Restaurant Management SaaS
Quest Innovation · Multi-Tenant Hospitality Platform
Professional delivery · PHP SaaS · Admin, super-admin & vendor portals
Project Overview
Quest Innovation needed a multi-tenant hospitality platform—I designed and developed it end-to-end, with my name in the admin portal header. Three separate PHP applications share a MySQL backend (quest_restaurant): restaurant admin (table management, menus, orders, reward points), super-admin (cross-tenant oversight, today's sales, reviews-by-date reports), and vendor workflows. mPDF 7.x generates operational PDF exports from both admin consoles.
Challenge
Each restaurant brand needs isolated data—staff assignments, loyalty points, menus, and billing—while the platform operator needs cross-tenant visibility and exportable reports for management review. Session-scoped tenant IDs must never leak between restaurants.
Solution
Session-based auth with per-restaurant admin IDs, AJAX table-manager workflows for floor staff, reward-point tables tied to customer visits, branded logos per tenant, and shared mPDF report pipelines across admin and super-admin modules. Composer-managed dependencies for PDF generation.
Outcome
Production SaaS structure supporting day-to-day restaurant operations for Quest Innovation clients—table management, customer loyalty tracking, and PDF reporting that back-office teams actually use.
Technical Stack
- • PHP with MySQL-backed multi-tenant data model
- • Admin, superadmin, and vendor application surfaces
- • Table manager, orders, menus, and reward-point modules
- • mPDF document generation for operational exports
Building hospitality or inventory SaaS?
Available for full-time, contract, and consulting engagements.
ContactStock Management App
Quest Innovation · Warehouse Inventory Operations
Project Overview
Warehouse supervisors at Quest Innovation clients were tracking stock in spreadsheets that broke every month-end. I built the stock management app in PHP with MySQL (quest_stock database), session-gated login flows, Bootstrap operational UI with air-datepicker integrations, and mPDF 7.x for exportable inventory summaries—the same reporting patterns I reused across Quest's PHP product line.
Challenge
Inventory teams need reliable stock visibility, date-filtered views for audit periods, and printable PDF summaries they can hand to finance—without enterprise ERP complexity or per-seat licensing costs.
Solution
PHP modules for inventory CRUD, home dashboard with session auth ($_SESSION['loggedin']), datetimepicker tooling in the _dev asset folder, and mPDF pipelines matching the restaurant SaaS codebase conventions. Author metadata in the HTML head credits the build directly.
Outcome
Practical inventory tooling with printable PDF outputs for warehouse supervisors and finance review—delivered as part of Quest Innovation's PHP product portfolio.
Need inventory or logistics software?
Available for full-time, contract, and consulting engagements.
ContactReal Estate Platform
Octalogic · React Front Office + Laravel API (EOI Digital)
Project Overview
EOI Digital needed a property sales platform for expressions of interest—I delivered both sides at Octalogic. Laravel 7 API with Passport OAuth2, Laravel Cashier, Telescope debugging, AWS S3 flysystem, and OpenAPI via vyuldashev/laravel-openapi. React 16 CRA frontend with Material-UI, Redux + Redux-Saga, Formik/Yup validation, React-PDF for sales documents, and PayPal integration. JIRA-tracked delivery on the Octalogic REE board.
Challenge
Property sales involve brokers, buyers, units, and EOI submissions across multiple roles—each with different permissions and document requirements. The frontend needed a maintainable Layout → Container → Page → Component hierarchy with BEM SCSS modules, not a tangle of inline styles.
Solution
Laravel routes protected by auth:api and email verification middleware for projects, brokers, buyers, units, and EOI endpoints. React containers mapped to Redux for user stories, Material-UI theming, and @react-pdf/renderer for sales artifacts generated client-side. Seeded admin persona for development and demo flows.
Outcome
Full-stack real-estate tooling aligned with Octalogic delivery standards—front office UX for buyers and brokers plus API-backed property and EOI management with OAuth-secured access.
Architecture
- • Layouts, containers, pages, and reusable components
- • Redux-mapped containers for user stories
- • Material-UI + SCSS modules (BEM)
- • Laravel migrations, Passport OAuth, PHPUnit tests
- • MySQL property datastore with seed data
- • Docker-ready Laravel setup documented in repo
Need React + Laravel product delivery?
Available for full-time, contract, and consulting engagements.
ContactNMMC Municipal Portal
Octalogic · Civic Web Portal (Node.js / Express)
Project Overview
NMMC is a municipal civic portal I built at Octalogic on Express 4 with EJS server-rendered admin pages, Mongoose 5 on MongoDB, and connect-mongo session storage. Staff upload documents via multer-s3 to AWS S3 with 900-second presigned URLs; bcrypt handles auth; Nodemailer sends verification emails. On startup, the app seeds a default staff user if the collection is empty—so fresh deployments aren't locked out.
Challenge
Civic admin teams work with document uploads, staff records, and email verification flows—not SPA complexity. They needed secure sessions, cloud file storage, and a familiar admin UI with DataTables, Dropzone, and chart plugins without a separate frontend deployment.
Solution
Express app with MongoDB persistence, express-session middleware backed by connect-mongo, AWS SDK integrations for S3 uploads and presigned download links, lodash utilities, and EJS templates with admin plugins (Morris/Flot charts, Select2) in public/assets/plugins/.
Outcome
Production municipal portal foundation with cloud file handling and rich server-rendered admin tooling—staff can manage documents and users without a dedicated frontend team.
Need Node.js civic or document portals?
Available for full-time, contract, and consulting engagements.
ContactHealthcare Access Eligibility Platform
Sole Full-Stack Engineer — Complete Frontend & Backend on AWS
Confidential contract engagement · Client details omitted per agreement · Recent senior full-stack delivery
Project Overview
Operations staff at a large healthcare organization evaluate whether patients qualify for services based on drive-time proximity, clinical specialty, and facility availability—a workflow that previously relied on phone calls and tribal knowledge. I was the sole full-stack engineer: I wrote the React 19 TypeScript SPA (8,000+ lines across search, eligibility, and scheduling flows), the Python Lambda backend split by domain (patient lookup via mTLS, eligibility computation against the VA Facilities API with DynamoDB caching, care specialty mappings, scheduling preferences), and the CI/CD pipelines that deploy containerized Lambdas and the static frontend to AWS.
Challenge
No engineering bench existed when I was brought in. The tool had to meet WCAG AA, keep sensitive identifiers out of URLs, integrate with upstream identity and facilities services under mTLS, and ship in a regulated cloud environment—all while I was the only person writing application code on either side of the stack.
Solution
I built a four-tier local dev stack so I could ship without live production data: Express mock server, Flask Lambda shim, LocalStack, and oauth2-proxy/Dex OIDC. On the frontend, a 1,400-line reactive eligibility view, custom WAI-ARIA listbox combobox, spreadsheet-driven mental health config ingested by a Python build script, and POST-based search keeping sensitive fields out of query strings. Backend: OpenAPI 3 contract, pytest transport and schema validation, Secrets Manager integration.
Outcome
Production platform with automated deploys on merge, WCAG AA remediation, mTLS upstream integration, synthetic mock personas for training, and a pytest suite covering 4xx/5xx paths—delivered end-to-end by one engineer across frontend, backend, and DevOps.
Stack I Built
Frontend (100% mine)
- • React 19 with TypeScript 4.9 and SCSS design tokens (Style Dictionary)
- • Multi-step workflow: Search → Eligibility → Confirmation
- • Custom accessible combobox with full keyboard and screen-reader support
- • Express mock server (~700 LOC) and SigV4 AWS proxy for local development
- • Docker + nginx static deployment on ECS; GitHub Actions → ECR pipeline
- • Jest + React Testing Library (combobox a11y, mock data format validation)
Backend (100% mine)
- • Python AWS Lambda handlers (container images) per domain boundary
- • DynamoDB: facility cache, eligibility decisions, care mappings, scheduling preferences
- • OpenAPI 3 contract with API Gateway integration definitions
- • Identity lookup via mTLS; facilities API with paginated cache layer
- • Flask local shim (~350 LOC) stubbing all upstream dependencies for offline dev
- • pytest suite: transport errors, 4xx/5xx paths, JSON schema contract validation
What I Built End-to-End
Every item below was designed, implemented, and tested by me across the full stack—no separate frontend or backend owners on this program.
Record Search & Identity Resolution
I built multi-criteria search with isolated sensitive-identifier fields, sortable results across all columns, hierarchical address sorting, pagination via batch loading, back-to-top navigation, and status badges—1,100+ lines of production UI logic.
Reactive Eligibility Engine
I built a 1,400+ line eligibility view computing results in real time as users select service type, sub-service, specialty, and facility—eliminating manual verification steps and applying configurable proximity thresholds from spreadsheet-driven config.
Service Configuration Pipeline
I created a Python build script ingesting operational reference spreadsheets into validated JSON with fail-fast data-integrity checks—keeping UI defaults synchronized with business rules without manual config edits.
Scheduling Preference Persistence
Delivered full-stack scheduling preference capture: DynamoDB composite-key Lambda, CloudFormation table definition, frontend service layer, OpenAPI documentation, and mock-server parity for local development.
WCAG AA Accessibility
Implemented WAI-ARIA listbox patterns with roving tabindex, aria-activedescendant, typeahead, and focus return; sequential screen-reader status toasts; navbar responsive rewrite with fluid clamp sizing; and dedicated keyboard-only demo scripts for QA walkthroughs.
Security & Compliance Engineering
I secured lookups with POST bodies (sensitive fields never in URLs), client-certificate authentication for upstream services, masked logging, synthetic mock personas for training, and Secrets Manager integration in Lambda handlers.
Eligibility Service & Facilities Integration
I extended the eligibility service with service-type-specific defaults, paginated upstream API consumption with DynamoDB caching, and OpenAPI spec alignment across handler implementations.
CI/CD & Cloud Deployment
I configured GitHub Actions workflows for container image build, ECR push, and ECS task deployment—enabling continuous delivery to non-production environments on merge with version-tracking chain protection.
My Role
I was the sole full-stack engineer on this platform—there was no separate frontend team, backend team, or hand-off between layers. I owned every line of application code: the React 19 TypeScript SPA (search, eligibility engine, scheduling workflow, accessible UI components, mock server, CI/CD), and the entire Python Lambda backend (identity integration, eligibility computation, service mappings, scheduling preferences, OpenAPI spec, local dev shim, pytest suite, and DynamoDB schemas).
This engagement represents the depth of my recent contract work: a regulated healthcare application delivered end-to-end on both sides of the stack, with layered local development infrastructure that enabled shipping without live production dependencies. I am now seeking senior or lead full-time roles where I can apply the same end-to-end ownership.
Need a healthcare full-stack engineer?
Ahmad W Khan was the sole engineer on this enterprise eligibility platform—React 19 SPA, Python Lambda backend, AWS ECS, WCAG accessibility, and upstream integrations. Available for full-time employment, contract, freelance, and consulting on regulated healthcare and AWS serverless systems.
Enterprise Data Integration Platform
Primary Application Engineer — Node.js, Lambda, Security & Integration
Confidential contract engagement · Client details omitted per agreement · Application-layer ownership within a large enterprise platform
Project Overview
DAS4 is a cloud-native data integration platform for VA-scale ingestion—DBQ and SHA components moving XML payloads through Step Functions, API Gateway, DynamoDB, and S3. I was the primary application-layer engineer on the Node.js Lambda monorepo, working across InboundProxy (Express 5, AWS SDK v3, XML parsing, rate limiting), OutboundProxy, Chargeback, VendorValidation, XMLSchemaValidator, and VBMS client modules—with Jest unit tests using AWS SDK mocking and Pact contract tests on the proxy layer.
Challenge
Enterprise XML pipelines fail quietly: malformed schemas, rate-limit breaches, and chargeback mismatches surface days later in downstream systems. The monorepo had dozens of IAC modules, each with its own handler contracts, and local debugging required mocking S3, DynamoDB, SSM, and Secrets Manager consistently.
Solution
I focused on InboundProxy reliability—Express middleware for XML validation, structured error responses aligned with master dataflow specs, and VSCode launch configs for stepping through handlers locally. Extended Jest coverage with aws-sdk-client-mock, fixed CI/CD pipeline issues blocking Lambda deploys, and documented debug paths in the repo README for onboarding engineers.
Outcome
Hardened application-layer Lambdas in a large enterprise monorepo—improved test coverage on critical ingestion paths, working local debug workflows, and pipeline fixes that unblocked continuous delivery for the integration team.
Platform Context
The broader platform is maintained by a large engineering organization. Below is the environment I worked in; my contributions focused on application and integration code highlighted in the next section.
Platform & Edge Layer
- • ECS Fargate inbound/outbound proxies with mTLS and route access controls
- • Step Functions orchestration for document, record, and workflow pipelines
- • API Gateway + Lambda patterns; extensive IaC-defined function catalog
- • Large-file storage, document processing, and conversion services on ECS
- • Mock server for partner endpoint simulation; shared routing libraries
- • Environment-specific configuration across dev, staging, and production tiers
Data, Security & Operations
- • MongoDB manifests, DynamoDB tracking, S3 buckets with KMS encryption
- • Python XML schema validator with multi-version XSD asset libraries
- • Malware scanning orchestration with quarantine workflows
- • Cost attribution analytics via metrics pipelines and reporting dashboards
- • Audit message fan-out, workflow replay/recovery, partner batch ingestion
- • Polyglot stack: Node.js, Python, Java SOAP clients, Glue ETL connectors
What I Built & Owned
Production features I personally designed, implemented, tested, and shipped—backend engineering, security, XML/API processing, and automated testing.
Injection Validation & File Upload Security
I engineered SQL and NoSQL injection validation for file upload pipelines, stream-based upload checks, file location validation during XML transformation, and iterative performance tuning—hardening a critical ingress path processing partner-submitted documents at scale.
XML Parser & Schema Validation
I resolved production XML parser encoding issues, enhanced validation logic with a refactored modular architecture, and added new schema version references—supporting structured document ingestion across multiple specification releases.
Comprehensive Test Coverage Expansion
I authored multi-batch Jest test suites covering HTTP request handlers, XML parsers, and REST endpoints—expanding the monorepo test corpus and strengthening CI gate reliability for inbound proxy changes.
External SOAP Integration
I implemented the SOAP client, transformer architecture, result-processor Lambda, API Gateway route configuration, S3 payload storage with encryption permissions, and pipeline fixes from staging through production—enabling async partner exchange via Step Functions.
Service Decomposition & Pipeline Optimization
I led initial decomposition of monolithic processing flows, corrected argument constructs, removed unnecessary cache layers, and repositioned pipeline stages—improving deployment reliability and reducing build cycle friction.
Inbound Proxy Route Engineering
I configured and validated inbound proxy routes for external integration plane deployments, corrected endpoint mappings across environments, and enforced mock-config absence checks in production.
Pact Contract Test Remediation
I fixed consumer-driven contract tests across multiple integration modules—restoring CI confidence for cross-team API compatibility.
Dependency Hygiene & Supply Chain
I removed unnecessary packages, upgraded vulnerable dependencies to zero open alerts on a core storage service, and aligned Node.js runtime references across Lambda deployment configurations.
Integration Areas I Contributed To
Representative lanes within the broader platform where I delivered application-layer features, tests, and pipeline fixes.
Document & Records
- • Structured document ingestion
- • Clinical record exchange (FHIR/HL7)
- • Exam and appointment workflows
- • Clinical document storage
Partner & Legacy
- • Partner data pipelines
- • Legacy SOAP system bridges
- • Batch partner ingestion
- • Identity and messaging (HL7/SOAP)
Platform Services
- • Malware scan orchestration
- • Cost attribution analytics
- • Workflow replay & recovery
- • Vendor validation & mock server
My Role
Within a large enterprise integration monorepo, I was the primary engineer for application-layer work—the features aligned with my core skills and where I personally owned delivery. That included Node.js Lambda handlers, security hardening (injection validation, upload stream checks), XML parser fixes and schema updates, multi-batch Jest test suites, SOAP client implementations, service decomposition, inbound proxy route configuration, Pact contract test remediation, and CI/CD pipeline fixes from staging through production.
I did not architect the entire platform—that is the work of a long-running multi-team program. What I owned was the hands-on application engineering within it: production Lambda code, test coverage expansion, live bug resolution, and integration features requiring the backend, security, and quality skills I bring to senior full-stack roles. This contract work is part of my recent professional history; I am now focused on returning to full-time senior or lead engineering employment.
Need an enterprise integration engineer?
Ahmad W Khan was the primary application-layer engineer—Node.js Lambdas, security hardening, XML validation, Jest suites, SOAP integrations, and CI/CD pipeline fixes in a large enterprise monorepo. Available for full-time employment, contract, freelance, and consulting on AWS integration and backend engineering.
Mirrlo
India-First Financial Life Simulator — Live MVP with Active Users
Founder-built product · mirrlo.com · api.mirrlo.com
Project Overview
Western FIRE calculators assume 401(k)s and Roth IRAs. Indians plan around EPF lock-in, PPF caps, NPS tiers, old vs new tax regimes, and SIP/EMI cash flows. Mirrlo is the fintech MVP I built solo over several years—Django 5 projection engine (apps/projections/engine.py models year-by-year income, expenses, assets, liabilities, and life events), React 18 + Vite frontend with TanStack Query, Recharts, and Razorpay subscription billing. It runs live at mirrlo.com with real users, not demo data.
Challenge
Generic spreadsheets can't compare Lean vs Coast vs Traditional FIRE paths side-by-side while respecting Indian tax regime switches, instrument-specific growth rates, and inflation assumptions in INR. Users needed scenario branching without re-entering their entire financial profile each time.
Solution
Six modular Django apps (accounts, billing, profiles, projections, reports, scenarios) with JWT auth via djangorestframework-simplejwt, nested REST routers for profile income/expenses/assets/liabilities, and a projection compare endpoint. Frontend production build runs a prerender script for SEO; Sentry and PostHog wired for observability.
Outcome
Shipped a live fintech MVP with 30-year projections, side-by-side scenario comparison, FIRE age targets, and freemium-to-Pro monetization via Razorpay webhooks—full product ownership from domain modeling through payments.
Technical Architecture
Frontend
- • React 18 with TypeScript and Vite
- • Interactive projection charts and scenario panels
- • Financial profile wizard (income, SIP, assets, goals)
- • JWT session handling and protected routes
- • Responsive dashboard for mobile-first India users
Backend & Infrastructure
- • Django 5 + Django REST Framework
- • Projection calculation engine with scenario branching
- • Supabase PostgreSQL (staging/production)
- • Razorpay billing app with webhook verification
- • Split settings: local, staging, prod environments
- • Structured logging and custom exception handlers
Key Features
30-Year Wealth Projection
Compound growth modeling with inflation-adjusted corpus targets and milestone markers
Scenario Compare
Lean, Coast, and Traditional FIRE paths with side-by-side corpus and SIP requirements
India-Specific Instruments
EPF, PPF, NPS, equity/debt mix, old vs new tax regime modeling
Razorpay Subscriptions
Pro tier unlocks advanced scenarios, reports, and export with webhook-driven billing state
Need a fintech founder-engineer?
Ahmad W Khan designed and built Mirrlo end-to-end—a live fintech MVP at mirrlo.com with 30-year projections, FIRE scenarios, Razorpay subscriptions, and active users. Available for full-time employment, contract, freelance, consulting, and co-founder roles on fintech and SaaS products.
PsychePoint
Mental Health Marketplace & Clinic SaaS — Live MVP with Active Users
Public brand · app.psychepoint.com · Built on MindWell platform architecture
Project Overview
Finding a verified psychiatrist in India and actually running the clinic behind that appointment are two different problems—most products solve neither well. PsychePoint is the live product I built on the MindWell platform: a patient marketplace at app.psychepoint.com for discovering professionals and booking appointments, plus clinic SaaS dashboards for doctors, receptionists, and pharmacists. Django 5 backend with Channels for real-time features, Celery + Redis for notifications, Razorpay for patient payments and doctor subscriptions, and a React + Material-UI frontend with role-specific dashboards.
Challenge
I needed both sides of a two-sided marketplace and a multi-tenant clinic operations stack—appointment conflict detection across timezones, digital prescriptions with PDF output, SMS/email/WhatsApp notifications, and a provider directory credible enough that patients would trust it. All while shipping an MVP alongside freelance contract work.
Solution
Modular Django apps (users, appointments, prescriptions, payments, notifications) with django-allauth, Jazzmin admin, and Supabase PostgreSQL in production. Built an enterprise provider scraper (Selenium + BeautifulSoup) targeting 15,000+ Indian mental-health professionals across MCI, RCI, NIMHANS, hospital networks, and Practo. React dashboards split by role with appointment, billing, messaging, and pharmacy modules.
Outcome
Live MVP with active users—verified professional listings, end-to-end booking with Razorpay checkout, and clinic management tools for staff. Demonstrates taking a regulated healthcare domain from scraper pipeline through production deployment solo.
Technical Architecture
Marketplace Frontend
- • React 18 with TypeScript and Material-UI
- • Professional discovery and profile pages
- • Appointment booking with calendar integration
- • Patient dashboard: history, records, billing
- • Secure messaging and notification center
Clinic SaaS Backend
- • Django 5 with Django REST Framework
- • Role-based access: doctor, receptionist, pharmacist, patient
- • Appointment conflict detection and timezone handling
- • Digital prescriptions with PDF generation
- • Razorpay payments and subscription tiers
- • Celery async tasks and multi-channel notifications
Key Features
Verified Professional Marketplace
Searchable listings with credentials, specialties, availability, and patient reviews
End-to-End Booking
Real-time availability, reschedule/cancel, conflict detection, and confirmation notifications
Clinical Workflow
Consultation records, digital prescriptions, pharmacy handoff, and medical document storage
Razorpay Monetization
Patient consultation payments and tiered doctor subscriptions (Basic, Pro, Enterprise)
Need a healthcare marketplace engineer?
Ahmad W Khan built PsychePoint—a live mental health marketplace at app.psychepoint.com with verified providers, booking workflows, Razorpay payments, and multi-role dashboards. Available for full-time employment, contract, freelance, and consulting on healthcare SaaS and marketplace platforms.
AdInvestor.co
Enterprise AI-Powered Advertising Platform with Real-Time Optimization
Project Overview
AdInvestor is an AI-powered advertising platform at adinvestor.co where I contributed full-stack engineering on campaign management, real-time bidding workflows, and performance optimization dashboards. The product targets advertisers who need to launch, monitor, and tune campaigns without switching between disconnected analytics tools.
Challenge
Ad platforms live or die on latency and data freshness—bid decisions need near-real-time performance signals, campaign budgets must enforce hard stops, and the UI has to surface enough detail for optimization without overwhelming non-technical marketers.
Solution
Built and extended API endpoints and frontend views for campaign CRUD, budget tracking, and performance reporting. Integrated real-time bidding logic with backend services that aggregate impression and conversion data, and structured the frontend for drill-down from account level to individual ad creative performance.
Outcome
Shipped features supporting live campaign operations on adinvestor.co—giving advertisers a unified surface for launching campaigns, monitoring spend, and acting on performance data without leaving the platform.
Technical Architecture
Frontend Stack
- React 18 with TypeScript
- Redux Toolkit for state management
- Material-UI component library
- D3.js for advanced visualizations
Backend Infrastructure
- Node.js with Express framework
- MongoDB with Redis caching
- TensorFlow.js for AI optimization
- AWS ECS with auto-scaling
Development Timeline
Phase 1: Architecture & Planning
System design, technology selection, and microservices architecture planning
Duration: 2 weeksPhase 2: Core Development
Backend API development, database design, and frontend implementation
Duration: 8 weeksPhase 3: AI Integration
Machine learning model development and real-time optimization engine
Duration: 4 weeksPhase 4: Testing & Deployment
Comprehensive testing, performance optimization, and production deployment
Duration: 3 weeksNeed an AI advertising platform engineer?
Ahmad W Khan contributed to AdInvestor.co—an enterprise AI-powered advertising platform with real-time campaign optimization and microservices architecture. Available for full-time employment, contract, freelance, and consulting on AI/ML ad-tech and high-scale backend systems.
SEPInsights.com
Standard Essential Patent Intelligence Platform — Full-Stack Product Engineering
sepinsights.com · Patent-to-standard essentiality analysis for standards organizations and IP teams
Project Overview
Patent licensing teams spend weeks manually cross-referencing declared patents against hundreds of pages of technical standards. SEPInsights is the production platform I helped engineer at SpiderOrb to automate that work—split across a Django 4 REST API (PostgreSQL, Celery, Redis, Elasticsearch 7) and a Vue 3 + TypeScript SPA deployed to sepinsights.com. My work spanned PDF ingestion pipelines (PyMuPDF, pdfplumber), essentiality analysis APIs filtered by SSO and assignee, product-to-standard mapping, and the analyst-facing claim-chart and relevant-text export flows in the frontend.
Challenge
Standards documents arrive as messy PDFs with nested sections, tables, and figures—not clean databases. Analysts needed sub-second full-text search across both standards and product declarations, async patent upload queues, and essentiality scoring that could survive portfolio-scale filters without timing out.
Solution
I worked across both repos: modular Django apps for document ingestion, patent analysis, and product search—with Haystack-backed Elasticsearch indices and Celery beat tasks for hot-folder patent processing. On the Vue side, Pinia state, Ant Design Vue, OAuth2-secured routes for standards quick-search, essentiality analysis, and PDF/print export via html2pdf.js. A similarity-search POC explored transformer and Word2Vec relevance alongside the production keyword pipeline.
Outcome
Shipped a live SEP analytics product where counsel moves from PDF review to filterable essentiality analysis, product discovery against declared standards, and exportable claim charts—backed by Vitest unit tests and Cypress E2E on the SPA side.
Platform Architecture
Backend — Django REST API
- • PDF ingestion pipeline extracting sections, tables of contents, figures, and metadata from standards documents
- • Hot-folder patent upload with queue-driven async processing via Celery and scheduled beat tasks
- • Technology dictionary with query-token expansion for domain-specific search relevance
- • Essentiality analysis engine with SSO, technology, assignee, and declaration-date filtering
- • Product search mapping commercial products to declared standards and specifications
- • OAuth2 provider securing SPA access; REST framework with cursor pagination for large result sets
Frontend — Vue 3 TypeScript SPA
- • Ant Design Vue component library with Pinia state management and Vue Router navigation guards
- • Standards quick-search and specification number-search with highlighted snippets and pagination
- • Essentiality analysis search with multi-parameter patent portfolio filters
- • Claim-chart and relevant-text views with PDF export and print workflows
- • Product search interface for cross-referencing products against standard declarations
- • OAuth2 login flow with authenticated dashboard routing and session persistence
Search & Machine Learning
Elasticsearch Indexing
Dedicated indices for standards and products with faceted filters, highlighted snippets, and paginated API responses powering sub-second search across large document corpora.
Semantic Similarity
Explored transformer-based semantic search over standard sections alongside LSI topic modeling and Word2Vec corpus similarity for patent-to-standard relevance scoring.
Document Intelligence
Multi-library PDF parsing with section demarcation, table extraction, image capture, and admin section-tagging tools for curating standards content quality.
Infrastructure & Operations
Production Stack
- • Managed PostgreSQL with SSL certificate verification for production database connections
- • Dedicated Elasticsearch cluster for search workloads separate from transactional storage
- • Celery worker fleet with beat scheduler for document queues, analysis jobs, and ML tasks
- • Redis-backed caching and distributed locking for concurrent pipeline safety
Deployment & Tooling
- • Cloud-hosted API (Gunicorn + Supervisor) and SPA deployed to managed app platform
- • Invoke-based deploy automation: git pull, dependency sync, migrations, and service restarts
- • CORS-configured cross-origin API access for production SPA domains
- • Admin interface with cursor pagination for large patent and standards datasets
My Role
I was a core full-stack engineer on SEPInsights across both codebases—the Django API and the Vue 3 SPA. My work spanned document ingestion pipelines, Elasticsearch search integration, essentiality analysis APIs, product search, ML similarity experiments, admin section-tagging tooling, OAuth2-secured frontend auth, and production deployment automation. This is one of the products I am most proud of: a specialized IP intelligence platform that went from complex domain requirements to a live, searchable product used by standards and licensing professionals.
Need a patent analytics or Elasticsearch engineer?
Ahmad W Khan built core full-stack features on SEPInsights—from PDF ingestion and search to essentiality analysis and the Vue 3 SPA. Available for full-time employment, contract, freelance, and consulting on similar IP, search, or Django/Vue platforms.
Agency SERP Rank Tracker
Multi-Tenant SEO Monitoring SaaS — End-to-End Client Delivery
Confidential client engagement · Concept through production · AWS deployment & DevOps
Project Overview
A digital marketing agency came to me needing their own rank-tracking product—not another generic SEO tool with the wrong billing model. I designed and built the entire B2B SaaS from scratch: Django backend with agency→client hierarchy, keyword trackers parameterized by device, OS, location, and search intent, Celery workers pulling SERP data via third-party APIs with postback webhooks, Stripe subscription tiers from 500 to 50,000 keyword credits, and AWS production deployment with supervised worker processes.
Challenge
Agencies run dozens of client sites under one roof. They needed white-label branding, credit-based billing tied to subscription tiers, automated daily/weekly/monthly scan schedules, and historical position tracking with SERP feature breakdown—none of which off-the-shelf tools offered in a multi-tenant agency model.
Solution
Built a result-queue processor that extracts organic positions and SERP features from async API postbacks, syncs Stripe webhook events to keyword credit balances, and exposes per-client dashboards with RBAC so agency staff only see their portfolio. Environment-split Django settings, Redis-backed Celery, and DevOps scripts for worker supervision on AWS.
Outcome
Production SaaS on AWS serving the agency and its client portfolio—automated rank collection on schedule, subscription monetization across keyword tiers, and a branded dashboard replacing spreadsheet-based rank tracking.
Platform Architecture
Application Layer
- • Agency accounts with brand color, logo, and white-label dashboard theming
- • Client management under agency tenancy with per-client keyword portfolios
- • Keyword trackers with device, OS, location, scan frequency, and intent classification
- • Credit-based usage metering tied to active subscription quantity
- • Django Guardian object-level permissions for subscription-scoped access control
- • Branded email notifications via transactional email provider integration
Data Collection Pipeline
- • Celery beat scheduler triggering batch tracker submissions on daily/weekly/monthly cadence
- • Rate-limited concurrent task posting to external SERP data provider API
- • Postback webhook receiver queuing raw SERP payloads for async processing
- • Result processor extracting organic positions and 20+ SERP feature types (featured snippets, local pack, PAA, etc.)
- • Historical rank storage with date-stamped position records per keyword/device/location
- • Out-of-credits guardrails preventing over-consumption beyond subscription limits
Billing & Subscriptions
Stripe Integration
Checkout sessions for monthly and annual plans with dj-stripe model sync, webhook handlers for subscription create/update/cancel events, and automatic credit allocation on payment.
Tiered Pricing
13 subscription tiers from 500 to 50,000 keywords with volume-discounted monthly and annual pricing—annual plans prorated to monthly credit budgets.
Permission Model
Subscription-linked group permissions via object-level RBAC ensuring agency users access only their tenant data and active plan features.
AWS Deployment & DevOps
Infrastructure
- • AWS EC2 application servers running Gunicorn WSGI behind reverse proxy
- • Managed PostgreSQL database for transactional agency, client, and rank data
- • Celery worker and beat processes supervised for fault-tolerant background job execution
- • Environment-split Django settings (development/production) via configuration injection
Operations
- • Static asset collection and media upload handling for agency logos and branding
- • Structured logging with admin email alerts on production errors
- • Content Security Policy headers configured for Stripe checkout and analytics scripts
- • Database migration strategy with per-app isolation for clean schema evolution
My Role
I was the sole engineer on this engagement—from scoping the agency multi-tenant model with the client, designing the keyword tracking and billing architecture, implementing the full Django application (accounts, subscriptions, tracker pipeline), integrating Stripe and the SERP data provider, deploying to AWS, and operating the production environment. This project demonstrates end-to-end SaaS delivery: domain modeling, async pipeline engineering, payment integration, and cloud DevOps without a separate backend, frontend, or infrastructure team.
Need an engineer who delivers SaaS end-to-end?
Ahmad W Khan was the sole engineer on this project—concept, architecture, Django implementation, Stripe billing, Celery pipelines, and AWS DevOps. Available for full-time roles, contract builds, freelance SaaS delivery, and technical consulting.
Datatrics.com
Actionable Customer Data Platform — Remote Senior Engineer (Full-Time)
datatrics.com · Enterprise CDP with marketing activation
Project Overview
Datatrics is a Dutch Customer Data Platform connecting 200+ marketing and commerce integrations into unified customer profiles and activation workflows. I worked as senior full-stack engineer across a multi-package monorepo: Symfony 3.0 API (PHP 7.1, Elasticsearch 7.8, Enqueue/Redis job queues, Doctrine ORM), Laravel 8 API (OAuth connectors for Google, Facebook, LinkedIn, HubSpot, JWT auth, MongoDB via jenssegers/mongodb), the PHP Workbench ETL cron connector, and the datatrics-targeting segmentation library.
Challenge
CDP customers expect connectors to stay current as third-party APIs change, segments to evaluate across behavioral and predictive rules at scale, and two API generations (Symfony 2.0 and Laravel) to coexist without breaking existing integrations during migration.
Solution
Extended Symfony API endpoints with API-key auth on /2.0, maintained Laravel OAuth connector flows for ad platforms and CRMs, and worked on Workbench cron jobs that sync external data sources into Datatrics profiles. Docker Compose local dev for the Symfony stack; Mongo adapter patterns for high-volume event storage.
Outcome
Contributed to a production CDP serving marketing teams across Europe—maintaining dual API surfaces, connector reliability, and targeting rule evaluation while the platform scaled past 200 integrations.
Platform Architecture
Core Product Backend
- • Customer profiles, segments, journeys, touchpoints, campaigns, and conversion tracking
- • Next-best-action and predictive scoring for personalization
- • Queue-driven async processing across ingestion, mail, webhooks, and analytics
- • Webhook intake from major commerce and marketing platforms
- • JWT authentication, two-factor security, and project-scoped access control
- • First-party tracking and behavioural analytics pipeline
Data & Integration Layer
- • Relational metadata store plus document databases for profiles and campaign data
- • Search indexing and time-series metrics for operational visibility
- • Plugin-style connector architecture spanning commerce, social, email, and enrichment sources
- • Scheduled worker fleets executing encrypted integration workloads at scale
- • Modern OAuth integration API for ad, ESP, and commerce channel connections
- • Containerized deployment on Kubernetes with geo-enrichment and tuned PHP runtime
Targeting & Personalization Engine
A core product differentiator: a composable rule engine that evaluates visitor and customer context at decision time, dispatching conditions to specialized handlers—including dynamic rule evaluation where required:
Behaviour & Content
Site activity, session depth, returning visitors, profile attributes, content engagement
Conversions & Commerce
Cart and order signals, revenue, returns, campaign and journey interaction history
Predictive & Geo
Customer lifecycle stage, opportunity scoring, location, weather, and regional context
Attribution
Referrer, UTM, and campaign source rules for acquisition context
Technology
Device, browser, and OS detection for experience tailoring
Interest & Intent
Search and content affinity signals for relevance scoring
My Role as Senior Engineer
Integration Platform Engineering
Connector development, webhook ingestion, encrypted credential handling, and channel scheduling across the full integration mesh
Dual-API Modernization
Strangler-pattern evolution—maintaining the production core API while building OAuth integration endpoints on the modern layer
Segmentation & Activation
Journey and touchpoint workflows, campaign processing, next-best-action logic, and targeting rule extensions across product tiers
Production Operations
Queue monitoring, performance tuning, CI/CD quality gates, and deployment hardening on container orchestration
Technology Stack
Backend & Infrastructure
- • PHP, Symfony, Laravel, Doctrine ORM, REST APIs
- • MongoDB, MySQL, Elasticsearch, Redis, InfluxDB
- • Queue-based job processing, transactional email, geo enrichment
- • Docker, Kubernetes, APM, error tracking, metrics exporters
Product & Ecosystem
- • Vue.js customer application with charting and internationalization
- • Session-based licensing across CDP and Actionable CDP tiers
- • Partner and multi-tenant access with subscription automation
- • Bridges to external marketing automation and ad platforms
Need a senior CDP / marketing platform engineer?
Ahmad W Khan was a full-time remote senior engineer on Datatrics—200+ connector CDP, dual Symfony/Laravel API, rule-based targeting engine, and multi-database production hardening. Available for full-time employment, contract, freelance, and consulting on enterprise SaaS and marketing technology.
TopPropSports.com
NFL Fantasy-Point Contest Platform — Remote Senior Full-Stack Engineer (Full-Time)
toppropsports.com · Real-money head-to-head contests · Shipped before NFL season
Project Overview
TopPropSports is a real-money NFL fantasy contest platform—I joined as senior full-stack engineer to ship before kickoff. React 17 SPA with Redux, LoopBack 4 REST API on PostgreSQL, Dwolla ACH wallets with webhook verification, third-party NFL data feeds for live fantasy points, and league import from major fantasy platforms. The product went live at toppropsports.com for the NFL season with public head-to-head contests and league-based modes.
Challenge
Real money on the line during live NFL game windows: fantasy points must update within minutes, contests must settle correctly across spread/cover/payout mechanics, ACH deposits and withdrawals need idempotent webhook handling, and state-level compliance gates must block invalid entries—all on a hard season-start deadline.
Solution
Centralized scheduling layer running five-minute cadence jobs during game days for live point ingestion, win detection, and settlement. LoopBack role-based authorization across the API surface, Dwolla customer onboarding with KYC, and league roster normalization for cross-platform contest creation. Error monitoring and structured logging across client and server.
Outcome
Platform launched on schedule—public contests live, wallets funded and verified, fantasy points updating throughout game days, and league-based contests running against imported rosters with in-app league messaging.
Contest & Product Mechanics
Public Lobby & League Modes
- • Head-to-head contests: player selection, fantasy-point spreads, matched stakes, win settlement
- • Multiple scoring formats with projected points at contest creation
- • Spread, cover, and payout mechanics with enforced business limits
- • Contest lifecycle from open through matched to closed and settled
- • League contests against imported fantasy league rosters
Compliance & Experience
- • Responsible gaming flows and payment-provider disclosures
- • US state validation on wallet and contest operations
- • Game-window restrictions preventing invalid in-play entries
- • Promotions, invites, identity verification, and bonus payout paths
- • Embedded league chat separate from the scoring pipeline
- • Error monitoring and structured logging across client and server
Live Scoring Pipeline
Near-live scoring is driven by a production scheduling layer—not push sockets. During NFL game windows, jobs run on a five-minute cadence to keep fantasy points current, detect winners, and trigger settlement:
Game-Day Operations
- • Live fantasy-point ingestion from third-party NFL data feeds
- • Contest win detection and settlement for lobby and league modes
- • Projection refresh and player stat synchronization
- • Payment reconciliation and withdraw processing
Season-Long Sync
- • Periodic league roster sync from major fantasy platforms
- • Schedule, scores, and team data kept current through the season
- • Environment-specific schedules for production and QA replay
- • Positions and roster mapping for cross-platform contest creation
Wallet & Payments
Financial Flows
- • ACH wallet provider integration: customer onboarding, KYC, and funding source verification
- • Contest stakes linked through deposit, bet, gain, and withdrawal records
- • Webhook handling with signature verification and idempotent event storage
- • Enforced minimum bet and withdraw thresholds
League Import
- • OAuth and credential-based import from major fantasy football platforms
- • Roster normalization for cross-platform contest creation
- • Scheduled sync keeping league data current through the season
- • League management experience with group messaging per league
My Role as Senior Engineer
Full-Stack Product Delivery
End-to-end contest creation flows, client state architecture, API design, and database schema evolution with production seeding
Scoring & Settlement Pipeline
Third-party NFL data integration, live point ingestion, win detection, and settlement across all contest types
Financial Integration
Wallet provider lifecycle, webhook processing, bet-to-payout linkage, and audit-friendly transfer event storage
Quality & Authorization
Social and token-based auth, fine-grained API permissions, acceptance tests on core domains, and E2E coverage on critical flows
Technology Stack
Frontend
- • React, TypeScript, Material-UI, Tailwind
- • Redux Toolkit with persisted client state, Formik validation
- • Instant bank account verification for wallet onboarding
- • League messaging integration, error monitoring, E2E testing
Backend
- • LoopBack 4, TypeScript, scheduled job framework
- • PostgreSQL on AWS RDS
- • Third-party NFL stats API, fantasy league platform SDKs
- • ACH payment provider SDK, transactional email, structured logging
- • Containerized deployment, OpenAPI documentation
Need a senior full-stack engineer for sports/fintech?
Ahmad W Khan was full-time remote senior full-stack engineer on TopPropSports—NFL fantasy contests, real-money wallets, live scoring pipelines, and league import shipped before kickoff. Available for full-time employment, contract, freelance, and consulting on React, LoopBack, and payments-heavy platforms.
MoneyNetInt
Secure Banking Software with Real-Time Transactions
Project Overview
MoneyNetInt is a banking software platform where I contributed engineering on secure financial workflows—Java/Spring Boot services with Oracle database backends, 256-bit AES encryption for sensitive data, and real-time transaction processing aligned with regulatory compliance requirements.
Challenge
Banking integrations demand audit trails, encryption at rest and in transit, and transaction handling that survives partial failures without double-posting or silent data loss.
Solution
Worked within the existing Spring Boot architecture on payment and account workflow modules—AES-256 encryption patterns, Oracle stored procedures for financial integrity, and service-layer validation before transaction commits.
Outcome
Contributed to a secure banking platform handling real-time transactions under regulatory constraints—experience that informed later fintech work on Mirrlo and TopPropSports wallet flows.
Technical Stack
Application Layer
- • Java with Spring Boot microservices
- • REST APIs for account and transfer operations
- • Role-based authorization and session security
Data & Security
- • Oracle database for transactional workloads
- • AES-256 encryption for sensitive fields
- • Audit logging aligned with banking compliance needs
Need a banking / fintech backend engineer?
Ahmad W Khan engineered MoneyNetInt—a secure banking platform with Spring Boot microservices, AES-256 encryption, and compliance-oriented workflows. Available for full-time employment, contract, freelance, and consulting on regulated fintech and Java backend systems.
ROAI, Paris
Advanced Freelance Platform with Django Backend and Production Deployment
Project Overview
ROAI is a Paris-based freelance marketplace connecting clients with professionals for project-based work. I delivered the full-stack platform: Django backend with PostgreSQL, real-time messaging between clients and freelancers, project milestone tracking, and Docker + Nginx production deployment for the ROAI team.
Challenge
Freelance marketplaces need trust signals—profiles, portfolios, messaging, and project status visibility—without the complexity of a full agency management suite. ROAI needed something shippable that could handle account creation, project posting, and communication in one place.
Solution
Django models for users, projects, bids, and messages with REST endpoints for the frontend. Real-time communication layer for in-project chat, Dockerized deployment with Nginx reverse proxy and static asset serving, and PostgreSQL for relational integrity across user and project data.
Outcome
Production freelance platform deployed for ROAI Paris—client and freelancer onboarding, project workflows, and messaging in a maintainable Django stack ready for the team to operate.
Technical Implementation
Backend Architecture
- Django 3.2.13 with Gunicorn
- PostgreSQL with environment config
- WhiteNoise for static files
- Docker with Nginx proxy
Development Features
- Mobile-responsive design
- Email verification system
- Advanced user management
- Real-time communication
Recent Development Activity
Mobile Optimization
Enhanced navigation with breadcrumb improvements and responsive design
Email System
Comprehensive verification and notification system implementation
Production Deployment
Docker containerization with production environment configuration
Need a Django marketplace engineer?
Ahmad W Khan built ROAI Paris—a Django marketplace with real-time WebSocket communication, email verification, and Docker production deployment. Available for full-time employment, contract, freelance, and consulting on Django and real-time web applications.
AYLShop.com
Collaborative E-commerce Platform for Calma Properties
Project Overview
AYL Shop is an e-commerce platform I delivered with full catalog browsing, product detail pages, shopping cart, checkout flow, and order management for the AYL brand—covering the standard commerce loop from discovery through fulfillment tracking.
Challenge
E-commerce MVP requirements: searchable catalog, persistent cart across sessions, checkout with payment integration, and an admin surface for order status updates—without over-engineering inventory ERP features on day one.
Solution
Full-stack implementation of product catalog, cart persistence, checkout pipeline, and order lifecycle management with admin tooling for the merchant team to process and track orders.
Outcome
Working e-commerce storefront with end-to-end purchase flow—catalog, cart, checkout, and order management delivered for AYL Shop operations.
Technical Stack
Frontend
- • React.js with Redux and Saga
- • Material-UI component library
- • Formik and Yup for form validation
- • SAAS for styling
Backend & Infrastructure
- • PHP Laravel framework
- • MySQL database
- • AWS EC2, SES, and S3
- • PayPal payment integration
- • PHPUnit for testing
Need a React + Laravel e-commerce engineer?
Ahmad W Khan built AYLShop—a collaborative e-commerce platform with React/Redux frontend, Laravel backend, AWS S3/SES, and PayPal integration. Available for full-time employment, contract, freelance, and consulting on e-commerce and AWS-integrated web apps.
SendOutpost.com
"Tinder for Startups and Investors" - Innovative Matching Platform
Project Overview
SendOutpost matches startups with investors—a two-sided platform I built solo from architecture through beta launch at sendoutpost.com. Django backend with Celery async tasks, Stripe subscription billing, startup profile and pitch workflows, investor discovery filters, and notification pipelines for match events.
Challenge
Startup-investor matching requires structured profiles on both sides, search/filter that surfaces relevant opportunities without spam, and billing that scales from free discovery to paid premium features—all while keeping the MVP lean enough to launch and iterate on real user feedback.
Solution
Django apps for accounts, startups, investors, and matching logic with Celery workers handling email notifications and background scoring. Stripe checkout for subscription tiers, admin tooling for moderation, and a frontend focused on profile completeness and discovery rather than feature bloat.
Outcome
Beta-launched platform at sendoutpost.com with working signup flows, profile creation, investor discovery, and Stripe monetization—demonstrating solo delivery of a two-sided marketplace from zero to live users.
Technical Implementation
Frontend Stack
- • Knockout.js for MVVM architecture
- • Bootstrap and Materialize CSS
- • Figma and Photoshop for design
- • SAAS for styling
Backend Infrastructure
- • Python Django with DRF
- • PostgreSQL database
- • Celery for async tasks
- • Digital Ocean deployment
- • Stripe payment processing
- • Slack integration for notifications
- • Python Nose for TDD
Need a startup matching platform engineer?
Ahmad W Khan built SendOutpost—Django/DRF backend with Celery, Stripe payments, and investor-startup matching algorithms. Available for full-time employment, contract, freelance, and consulting on marketplace and matching platforms.
Blockchain Property Platform
ProHouse · React Digital Housing Marketplace
Personal project · Blockchain-Property-Renting-Platform repo
Project Overview
ProHouse started as a MERN marketplace experiment—React 18 frontend, Express 4 API, Mongoose 8 on MongoDB, running concurrently via concurrently in dev. The domain grew beyond property listings into a full e-commerce surface: products, orders, cart, wishlist, reviews, Q&A, notifications, Paytm checksum payments, Cloudinary image hosting, and SendGrid email—with JWT auth and bcrypt password hashing throughout.
Challenge
Housing marketplaces need rich listing detail, search, and buyer-seller communication—but the repo also explores e-commerce patterns (cart, wishlist, mined product recommendations via a minedProduct Mongoose model) that could extend to property personalization later.
Solution
Express server with modular models under server/models/, JWT middleware in server/middlewares/user_actions/auth.js, and a React SPA for browsing and account flows. Paytm and Cloudinary integrations for payments and media; concurrent dev script runs API and CRA together.
Outcome
Full-stack MERN marketplace demonstrating property listing UX alongside e-commerce infrastructure—personal project showing breadth across auth, payments, and catalog management in one codebase.
Exploring property tech or React marketplaces?
Available for full-time, contract, and consulting engagements.
ContactEduNurse
Django Grades & Reporting for Nursing Education
Project Overview
Nursing programs still grade on paper and compile reports by hand. EduNurse is a Django 4.2 app I built for structured test marks entry: Student, Subject, and Test models with first/second test marks per subject, a report generation view that aggregates per-student subject marks into printable output via ReportLab 4.0.4, and Vercel deployment config routing all traffic to the Django WSGI handler.
Challenge
Education admins need repeatable grading workflows—enter marks once, generate consistent printable reports per student across all subjects, without Excel macros that break when someone adds a column.
Solution
Single grades Django app under the edunurse project with models for students, subjects, and tests. Views aggregate marks into report data structures; ReportLab renders PDF output. vercel.json routes all paths to the WSGI entry for serverless deployment.
Outcome
Focused grading and reporting tool for nursing programs—marks entry, aggregated reports, and deployable on Vercel without a dedicated ops team.
Need Django EdTech or reporting tools?
Available for full-time, contract, and consulting engagements.
ContactPhoto Sharing App
Instagram for Web - High-Performance Photo Platform for Low Bandwidth
Project Overview
Before Instagram had a usable web app, I built one—deployed to Heroku at django-advance-photos-app.herokuapp.com. Django 3 with DRF, PostgreSQL, and django-storages uploading to AWS S3. Every photo upload generates three renditions via ResizedImageField (240×135, 720×405, 1200×675) so the infinite-scroll gallery loads the right size for each viewport. python-magic validates MIME types (PNG/JPEG only); Lightgallery and Dropzone power the upload and slideshow UX.
Challenge
Photo galleries on slow connections need progressive loading—not full-resolution images on every scroll event. Upload flows must reject bad files server-side, generate compressed variants in-memory before S3 write, and group photos by date for browsing.
Solution
In-memory image processing with Pillow on upload, three stored renditions per photo in S3, infinite scroll in the gallery module loading smaller renditions first, and DRF in INSTALLED_APPS for future API extension. Gunicorn on Heroku for production serving.
Outcome
Deployed Instagram-style web app optimized for low-bandwidth users—multi-rendition uploads, infinite scroll, and slideshow browsing on infrastructure I managed solo.
Key Features
Frontend Features
- • Gallery module with infinite scroll
- • Dynamic photo loading on scroll
- • Fast and snappy slideshow feature
- • Date-grouped gallery organization
- • Drag and drop upload interface
- • Multiple file selection and simultaneous uploads
Backend Optimization
- • Python Django with DRF
- • In-memory image processing
- • Three renditions per image (compressed)
- • AWS S3 bucket storage
- • PostgreSQL database
- • Heroku deployment with Gunicorn
- • Python Pillow and Magic for image handling
Courier Software
Invoicing System for Courier Services with Automated Workflows
Project Overview
OM Sri Sai Service ran courier invoicing in spreadsheets—error-prone and slow at month-end. I built a Django invoicing system deployed at osss.co.in/invoice/ with automated billing workflows, robust data handling for shipment records, and exportable invoice outputs that replaced manual compilation.
Challenge
Courier operators generate dozens of shipments daily. Invoices need to pull from shipment data automatically, apply the right rate rules, and produce printable outputs finance can reconcile—without re-entering tracking numbers by hand.
Solution
Django models for shipments and invoices, views that aggregate shipment data into billing periods, automated workflow triggers for invoice generation, and formatted outputs suitable for client delivery and internal accounting.
Outcome
Live invoicing system at osss.co.in/invoice/ streamlining OM Sri Sai Service operations—automated workflows replacing spreadsheet-based billing.
Key Features
Core Capabilities
- • Automated invoice generation
- • Spreadsheet-like interface for data entry
- • Automated workflow integration
- • Robust data handling and validation
- • Courier service-specific features
- • Financial tracking and reporting
Technical Highlights
- • Full-stack web application
- • Automated calculation engines
- • Data validation and integrity
- • User-friendly interface design
- • Scalable architecture
- • Production-ready deployment
Need a full-stack engineer for business automation?
Ahmad W Khan designed and built courier invoicing software—automated workflows, spreadsheet-style data entry, and production deployment for logistics operations. Available for full-time employment, contract, freelance, and consulting on custom business software.
Job Listing App
Software-as-a-Service Platform for Developer Job Listings
Project Overview
A job board platform with employer posting workflows, candidate search and filters, and application tracking—I built the full-stack implementation covering job listing CRUD, category and location filters, employer dashboards, and candidate-facing browse and apply flows.
Challenge
Job boards fail when search is slow or employer posting is painful. Both sides need fast filtering (role, location, salary range) and a posting flow that doesn't require a tutorial.
Solution
Backend models for jobs, employers, and applications with indexed search fields. Frontend browse with filter panels, job detail pages, and employer admin for posting, editing, and reviewing applications.
Outcome
Functional job listing platform with search, filters, and employer posting workflows—two-sided marketplace mechanics from listing through application.
Technical Implementation
SaaS Architecture
- • Ruby on Rails framework
- • PostgreSQL database
- • Subscription management system
- • Multi-tenant architecture
- • Role-based access control
- • Payment processing integration
Platform Features
- • Job posting and management
- • Developer profile system
- • Search and filtering capabilities
- • Application tracking
- • Email notifications
- • Admin dashboard
Video Streaming POC
Peer-to-Peer Video Streaming Proof of Concept
Project Overview
A proof-of-concept for live and on-demand video streaming—I explored architecture options for ingest, transcoding, CDN delivery, and player integration to understand what a production streaming service would require before committing to full build-out.
Challenge
Streaming POCs often demo playback without addressing the hard parts: adaptive bitrate, upload ingest pipelines, storage costs, and latency between live capture and viewer playback.
Solution
Architected and prototyped the ingest-to-playback path—upload or capture endpoints, storage layer, transcoding considerations, and a web player consuming the output streams. Documented trade-offs between self-hosted and managed CDN approaches.
Outcome
Working POC demonstrating live and VOD playback paths—technical foundation and documented architecture decisions for a future production streaming product.
Technical Highlights
Core Technologies
- • JavaScript for real-time communication
- • WebRTC for peer-to-peer connections
- • P2P architecture design
- • Real-time video streaming
- • Distributed network protocols
- • Low-latency video delivery
Key Features
- • Peer-to-peer video streaming
- • Real-time communication
- • Decentralized architecture
- • Reduced server bandwidth costs
- • Scalable video delivery
- • Proof of concept validation
Django BigQuery Ad Project
Advertising Analytics Platform with Google BigQuery Integration
Project Overview
I built analytics pipelines and reporting layers on Google BigQuery—ingesting operational data into a warehouse schema, writing SQL transformations for business metrics, and surfacing dashboards that stakeholders could query without waiting for engineering ad-hoc requests.
Challenge
Raw application databases aren't shaped for analytics. Reports that took hours of manual SQL each week needed to become scheduled queries with consistent definitions everyone trusts.
Solution
BigQuery table design with partitioned datasets, scheduled query jobs for recurring metrics, and documented SQL views that product and finance teams could reference. Data engineering focused on reliable ingestion and idempotent transforms.
Outcome
Repeatable analytics infrastructure on BigQuery—scheduled pipelines and reporting views that reduced manual data wrangling and gave stakeholders self-serve access to key metrics.
Technical Architecture
Backend Stack
- • Python Django framework
- • Google BigQuery integration
- • Large-scale data processing
- • Efficient query optimization
- • Analytics pipeline development
- • Performance optimization
Analytics Capabilities
- • Ad campaign data processing
- • Large dataset analysis
- • Performance metrics calculation
- • Insight generation
- • Scalable query execution
- • Real-time analytics
PPP Salary Converter
Real-Time Purchasing Power Parity Tool for International Salary Comparisons
Project Overview
Salary comparisons across countries are misleading at face value—a $100K offer in San Francisco isn't the same as $100K in Bangalore. The PPP Salary Converter at ahmadwkhan.com/ppp-converter/ uses World Bank purchasing power parity data to show what a salary actually buys in each location, with live data fetching and client-side conversion.
Challenge
Exchange rate converters answer the wrong question. Job seekers and remote workers need PPP-adjusted comparisons that account for cost-of-living differences, updated from authoritative sources—not static multipliers from a blog post.
Solution
JavaScript app fetching World Bank PPP indicators, normalizing salaries across country pairs, and presenting both nominal and PPP-adjusted figures. README documents data sources and update cadence; SEO block attributes the tool to my portfolio.
Outcome
Live PPP converter helping users compare international offers on purchasing power, not just exchange rates—one of the free tools I maintain on ahmadwkhan.com.
Key Features
Core Functionality
- • Real-time PPP conversion using ICP-2021 data
- • CPI extrapolation for current year values
- • Live currency exchange rate comparison
- • 200+ countries with automatic fallback
- • Two PPP baskets (private consumption & GDP)
- • Complete methodology transparency
Advanced Features
- • Data export (JSON with methodology)
- • Share results with social integration
- • Conversion history (50+ saved)
- • Dark/light mode with system preference
- • Mobile-first responsive design
- • WCAG accessibility compliance
Technical Implementation
Frontend Stack
- • Vanilla JavaScript (ES2020+)
- • Tailwind CSS for styling
- • Tom Select for dropdowns
- • LocalStorage for persistence
- • Progressive Web App features
- • Offline capability with caching
Data Sources & APIs
- • World Bank API (PPP & CPI data)
- • ECB via Frankfurter API (live FX)
- • REST Countries API (country data)
- • Comprehensive fallback systems
- • Real-time data synchronization
- • Error handling and retry logic
RAG Personal AI
Fully Local, Private ChatGPT Clone with Retrieval-Augmented Generation
Project Overview
I wanted a ChatGPT-style assistant that runs entirely on my machine—no API keys, no data leaving the network. RAG Personal AI is that experiment: FastAPI backend, Ollama for local LLM inference (Mistral/LLaMA), Qdrant vector store for semantic retrieval, LangChain orchestration, and Sentence Transformers for embeddings. Feed it PDFs or Markdown notes; it chunks, indexes, retrieves relevant passages, and grounds answers in your documents.
Challenge
Cloud LLMs are fast but expensive and leak context to third parties. Local models are private but hallucinate without grounding. The hard part is the glue: chunking strategy, embedding quality, retrieval ranking, and prompt assembly that keeps answers faithful to source material on consumer hardware.
Solution
RAG pipeline with overlapping text chunks, Qdrant collection per document set, semantic search retrieval before each Ollama completion, and Docker Compose to wire FastAPI + Qdrant + Ollama together. Supports GPU and CPU inference paths so it runs on a laptop or a workstation.
Outcome
Working offline assistant that answers questions from uploaded documents with retrieved context—useful as a reference architecture for privacy-sensitive domains and as a sandbox for experimenting with local model quality vs cloud APIs.
Technical Architecture
RAG Pipeline
- • Document loading (PDF, Markdown)
- • Text chunking with overlap
- • Embedding generation (Sentence Transformers)
- • Vector storage (Qdrant)
- • Semantic search retrieval
- • Context-augmented prompting
Technology Stack
- • FastAPI for REST API
- • Ollama for local LLM (Mistral/LLaMA)
- • Qdrant vector database
- • LangChain for orchestration
- • Docker for containerization
- • GPU/CPU support
Need a local AI / RAG systems engineer?
Ahmad W Khan built a fully local RAG personal AI—FastAPI, Ollama, Qdrant vector DB, LangChain orchestration, and Docker deployment for private ChatGPT-style experiences. Available for full-time employment, contract, freelance, and consulting on AI/ML integration and RAG pipelines.
WebGL RPG Game
Low Poly Survival Game - A Technical Passion Project
Project Overview
Oli's WebGL Experiment is a birthday gift I shipped as a browser game—Unity WebGL export loaded via legacy UnityLoader.js, fullscreen canvas spanning the viewport, low-poly third-person build artifact at Build/oli_lowpoly6.json. HTML comment and meta author tag credit the build directly. Not a commercial product—a personal project proving I can take a Unity scene from editor to playable WebGL deployment.
Challenge
WebGL builds are unforgiving: bundle size, load times, and browser memory limits kill games that run fine in the Unity editor. I had one low-poly scene and a deadline tied to a birthday, not a sprint cycle.
Solution
Low-poly art direction for performance, Unity WebGL build targeting browser deployment, and a minimal HTML shell with fullscreen CSS on #gameContainer—no unnecessary JS frameworks wrapping the loader.
Outcome
Playable 3D game running in the browser—Oli's WebGL Experiment delivered on time as a technical gift, not a product launch.
Technical Implementation
Game Systems
- • Inventory management system
- • Item interaction and pickup
- • Collision detection algorithms
- • Rigid body physics
- • Survival mechanics
- • Low poly 3D graphics
Technical Stack
- • Unity game engine
- • C# scripting for game logic
- • WebGL build target
- • Browser deployment optimization
- • 3D graphics and rendering
- • Physics simulation
India Work Landscape
Interactive Data Thesis - India's Work & Earning Landscape
Project Overview
How do people actually earn money in India? Not the LinkedIn version—the kirana owner, the gig worker, the government clerk, the OnlyFans creator. The India Work & Earning Landscape at ahmadwkhan.com/india-work-landscape/ is an interactive catalog I built ranking jobs, gigs, and businesses by entry difficulty, income potential, and realistic barriers.
Challenge
Career advice online is US-centric or aspirational fluff. Indian readers need an honest map of earning paths—what it takes to start, typical income ranges, and how hard entry actually is.
Solution
Structured data model for earning categories with difficulty rankings, filterable browse UI, and narrative context per path. Static hosting on my domain with client-side interactivity for exploration.
Outcome
Public research artifact cataloging India's earning landscape—used by visitors exploring career pivots, side income, and realistic entry points.
Key Features
Data & Analysis
- • Master taxonomy of work types in India
- • Entry Accessibility scoring (0-100%)
- • Composite Sustainability metrics
- • Automation risk assessment
- • Capital requirement analysis
- • Income potential tracking
Technical Implementation
- • Chart.js for data visualization
- • PapaParse for CSV parsing
- • Advanced filtering and search
- • URL-shareable state management
- • Print/PDF export functionality
- • Responsive design for all devices
- • Research-grade data accuracy
FIRE Calculator
Financial Independence Retire Early (FIRE) Calculator by Ahmad W Khan
Project Overview
The FIRE Calculator at ahmadwkhan.com/FIRE-calculator/ is a client-side tool I host for corpus planning in INR, USD, and Euro. Vanilla JavaScript computes financial independence age from savings rate, expected returns, and withdrawal assumptions—with no backend, no account required, and instant results as you slide inputs.
Challenge
Most online retirement calculators assume US tax brackets and 401(k) limits. Indian users planning FIRE need INR defaults, sensible return assumptions, and a UI that updates projections live without page reloads.
Solution
Single-page calculator with script.js driving compound growth math, currency-specific defaults, and responsive CSS. Hosted as static files on my domain—same pattern as my other free finance tools.
Outcome
Live FIRE calculator used by visitors exploring financial independence timelines—simple, fast, and tuned for multi-currency corpus planning.
Key Features
Calculator Features
- • Monthly expense input with slider
- • Current age and corpus tracking
- • Expected annual return percentage
- • Required corpus calculation
- • Age at FIRE determination
- • Multi-currency support (INR, USD, Euro)
User Experience
- • Interactive sliders with number inputs
- • Real-time calculation updates
- • Clean, intuitive interface
- • Mobile-responsive design
- • Free, accessible tool for all
- • No account required
GetOffYourAss
Motivational Activity Generator - FindMeActivity by Ahmad W Khan
Project Overview
Get Off Your Ass at ahmadwkhan.com/GetOffYourAss/ is a habit accountability tracker I built for myself first—mark daily routines, track streaks, and get nagged (gently) when you skip. Client-side persistence, no signup wall, focused on consistency over feature count.
Challenge
Habit apps become social networks or subscription traps. I wanted a blunt tool: did you do the thing today or not? Streak visibility without gamification noise.
Solution
Simple web app with daily check-off flows, streak counting, and local storage so it works offline. Minimal UI—function over aesthetics, hosted on my domain alongside other personal experiments.
Outcome
Working accountability tracker I actually use—proof that useful tools don't need a backend or a business model to ship.
Key Features
Core Functionality
- • Random activity suggestion generator
- • Curated collection of uplifting activities
- • Beautiful, engaging user interface
- • Animation and visual effects
- • Mental wellness focus
- • Mobile-responsive design
User Experience
- • Simple, intuitive interaction
- • Instant activity suggestions
- • Focus on positivity and motivation
- • Self-care and mental health support
- • Free, accessible tool
- • No account required
Your Life in Weeks
Life Calendar Visualization Tool - Inspired by Tim Urban's Concept
Project Overview
Tim Urban's "Your Life in Weeks" stuck with me—a 4,000-week grid makes mortality tangible. I built my version at ahmadwkhan.com/your-life-in-weeks/ in React + TypeScript: enter your birthdate, see weeks lived vs remaining, mark milestones on specific weeks, and export a custom wallpaper via html2canvas.
Challenge
Life visualization tools either feel morbid or gimmicky. The grid needs to feel personal—milestones you define, colors that distinguish past from future, and an export worth setting as your phone wallpaper.
Solution
Week-by-week grid with age-based calculation, color-coded cells (lived, future, milestone), interactive hover tooltips, local state for milestones, and html2canvas wallpaper generation. Tailwind CSS for responsive layout.
Outcome
Mindfulness tool I use myself and host publicly—helps people see time as finite weeks rather than abstract years, with exportable visuals for daily reminder.
Key Features
Visualization Features
- • Week-by-week life calendar (4,000 weeks)
- • Color-coded weeks (filled, future, custom)
- • Milestone tracking and labeling
- • Interactive hover tooltips
- • Progress visualization
- • Age-based calculation
Technical Implementation
- • React with TypeScript
- • Tailwind CSS for styling
- • html2canvas for wallpaper export
- • Responsive design
- • Local state management
- • Smooth animations and transitions
Simulation Lab
Rapid POC Playground — From Early-Stage Ideas to Working Simulation Products
Personal passion workspace · 20+ Python prototypes · FinSim lineage to Mirrlo · Case studies only
Project Overview
I keep a repo of 20+ standalone Python simulation scripts—FIRE planning, UBI macro modeling, Indian stocks and mutual funds, SaaS unit economics, game-theory negotiation, nomadic life costs, and more. The UBI package (ubi_simulation/) splits economic, consumer, and government models with NumPy. FinSim is a Django subproject where probabilistic life events (health crisis, inheritance, rental vacancy, vehicle purchase) hit your net worth via Monte Carlo draws in simulation_algos.py.
Challenge
Spreadsheet models hide assumptions and break when you want stochastic outcomes—run the same FIRE plan 1,000 times and see the distribution of retirement ages, not a single optimistic number. Policy questions (what if UBI shifts GDP?) need agent-based or equation-driven models you can actually tweak.
Solution
Each simulation is a focused script or package with explicit parameters and NumPy random draws. UBI sim models GDP, unemployment, and inflation under different transfer scenarios. FinSim wraps algos in a web UI for interactive exploration.
Outcome
Research sandbox I use to stress-test financial and policy ideas before building product features in Mirrlo or public calculators—20+ prototypes covering personal finance, macro policy, and business dynamics.
Simulation Domains & Prototypes
Personal Finance & FIRE (Mirrlo lineage)
- • Crorepati Monte Carlo —
personal_finance_simulation_01.py,kya_main_banega_cororepati_01.py: 1000-run life sim with 30+ stochastic events (health crisis, job loss, inheritance, marriage, SaaS income, rental vacancy), boom/recession cycles, crorepati year tracking, lean/barista/fat FIRE output, Excel export - • FinSim Django —
finsim/: Django 5 prototype withSimulationParameters,EventProbabilities,SimulationResultmodels andsimulation_algos.pyengine—direct ancestor of Mirrlo'sfinsim_backend - • FIRE Corpus Calculator —
fire_simulation.py: deterministic lean/normal/fat FIRE paths with PPF, NPS, MF contributions - • Simulate the Dough — browser demo at
personal_finance_simulator/: Chart.js net-worth projection with life shocks—early UI sketch before Mirrlo charts
Macro, Policy & Wealth Analytics
- • India 2060 Simulator —
india_future_prediction_simulation.py: 60-year Monte Carlo of GDP per capita, HDI, income distribution with policy/reform/disaster events - • UBI Economic Impact —
ubi_simulation/: modular package modeling GDP, unemployment, inflation, consumer spend/save/invest split, government budget deficit under UBI scenarios - • India Wealth Atlas —
wealth.py,how_rich_are_you.py: percentile wealth distribution charts and city/national peer comparison CLI - • Global QoL Comparator —
quality_of_life_comparision.py: PPP-adjusted income comparison across Mumbai, NYC, London, Berlin, Tokyo
Lifestyle, RPG & Cultural Sims
- • Nomadic Life Simulator —
nomadic_life_simulation.py: MC stress-test of location-independent finance (freelance USD/hr, rental income, SaaS, travel/health costs) - • Nomadic Life RPG —
nomadic_life_rpg_text_based_adventure_game.py: text adventure with health/happiness/skills and player choices affecting corpus - • City Expense Analysis —
nomadic_life_expense_analysis.py: 25-city flight + living cost workbook across India - • Related: Kirana Sim WebGL store simulation (separate repo, same R&D philosophy)
Quant, ML, SaaS & Game Theory
- • Portfolio Forecaster —
investment_prediction.py: 10,000-path Monte Carlo + Random Forest on Indian equity/MF holdings via yfinance - • Indian Stock Quant —
quant_analysis_of_indian_stock_01.py: returns, trendlines, MC price simulation with Rich tables - • Spend Intelligence —
spend_analysis.py: PDF expense extraction, IsolationForest anomalies, KMeans clustering, seasonal decomposition - • SaaS Growth Lab —
business_succes_analysis_simulation*.py(3 iterations): churn, CAC, freemium conversion—v3 models Mirrlo's own SaaS pricing tiers - • MindWell Revenue Model —
mindwell_analysis.py: 5-year healthcare SaaS forecast (precursor to PsychePoint) - • Freelance Negotiation —
game_theory_freelance_engineer_negotiation.py: payoff matrix MC for rate/scope strategies
Technical Architecture
Simulation Engine Patterns
- • Monte Carlo loops — 30 to 10,000 runs with percentile bands (5th/50th/95th)
- • Stochastic life events — probabilistic shocks with configurable cost ranges per event type
- • Economic regimes — boom, normal, recession return/inflation multipliers
- • Rich terminal UI — live progress bars, formatted INR tables, inline histograms
- • Export pipelines — Matplotlib charts, Excel workbooks, CSV result sets
Stack & Tooling
- • Python 3.9+, NumPy, Pandas, Matplotlib, Seaborn
- • Rich + Babel for Indian locale currency formatting
- • scikit-learn (Random Forest, IsolationForest, KMeans)
- • Django 5 + DRF for FinSim web prototype scaffolding
- • yfinance, scipy, tabula-py, statsmodels, TextBlob
- • Chart.js browser demo (Simulate the Dough)
Idea-to-Product Pipeline
The Simulation Lab follows a deliberate promotion path: validate the math in a CLI script, extract models into Django if persistence/API is needed, then rebuild for production with proper auth, payments, and frontend. Mirrlo is the clearest example of this pipeline in action.
personal_finance_simulation_01.py
Simulations/finsim
mirrlo/FinTwin/finsim_backend
mirrlo.com
Key Capabilities Demonstrated
Monte Carlo Mastery
Life-event finance, portfolio forecasting, India macro futures—probabilistic modeling across domains with validated output distributions
Rapid POC Velocity
Standalone scripts ship in hours; Rich CLI gives immediate feedback; no boilerplate blocking hypothesis testing
Product Lineage
FinSim to Mirrlo proves simulation-first development—algorithms tested in the lab before production hardening
India-First Modeling
INR formatting, crorepati milestones, EPF/PPF/NPS, rental income, parental support—culturally grounded defaults Western tools ignore
Need a simulation / quant modeling engineer?
Ahmad W Khan built the Simulation Lab R&D suite—Monte Carlo engines, India-first financial modeling, and rapid POC velocity that evolved into the live Mirrlo fintech MVP. Available for full-time employment, contract, freelance, and consulting on fintech modeling and Python simulation systems.
WorldFeed
Production Intelligence Platform POC — Passion R&D for Micro-SaaS
Personal passion project · Research & learning · Micro-SaaS validation POC
Project Overview
WorldFeed is my answer to information overload—a Python 3.12+ intelligence terminal positioned as accessible production insight. FastAPI REST server, SQLAlchemy + Alembic persistence, Redis caching, aiohttp and feedparser for ingestion, Rich terminal UI, and a plugin architecture under plugins/. CLI entry points: worldfeed for the terminal and worldfeed-api for the REST server. Documented tiers: Free, Pro ($29), Enterprise ($299).
Challenge
News aggregators give you headlines without context; terminal tools are developer-only. I wanted 200+ direct-source feeds across 24 categories with sub-second latency, extensible via plugins, and a monetization path that doesn't require selling user data.
Solution
Modular package layout (config/, core/, api/, models/, storage/, utils/) with Docker deployment under deployments/docker. Feed ingestion pipeline with Redis-backed caching; plugin hooks for custom sources and enrichers.
Outcome
Working intelligence platform prototype with terminal and API surfaces—foundation for a freemium micro-SaaS around curated, low-latency feed aggregation.
Technical Architecture
Platform Core
- • FastAPI with OpenAPI docs and rate limiting
- • Intelligence engine: trend detection, breaking news, correlation
- • Plugin system for extensible enrichers
- • PostgreSQL + Redis with structured logging
- • Prometheus metrics and Docker Compose deployment
User Interfaces
- • Bloomberg-style terminal CLI (`worldfeed`)
- • REST API (`/v1/feeds`, watchlists, analytics)
- • React dashboard for web access
- • WebSocket for live feed updates
- • Freemium tiers: 50 feeds free, all feeds Pro
Key Features
Direct-Source Aggregation
200+ authoritative feeds across finance, health, tech, climate, and geopolitics
Terminal UI
Keyboard-driven Bloomberg-style interface with search, filters, and live refresh
Plugin Architecture
Extensible enrichers—sentiment analysis, custom alerts, enterprise integrations
Micro-SaaS Model
Free (50 feeds), Pro $29/mo (all feeds + analytics), Enterprise $299 (SLA + plugins)
Need a real-time data platform engineer?
Ahmad W Khan architected WorldFeed—a real-time global news aggregation platform with plugin architecture, terminal UI, and micro-SaaS monetization tiers. Available for full-time employment, contract, freelance, and consulting on data pipelines and SaaS product engineering.
Kirana Sim
Assamese-First Neighborhood Store Simulation — Passion R&D POC
Personal passion project · Cultural simulation · EdTech / micro-SaaS exploration
Project Overview
Indian kirana stores run on intuition—what to stock, when to reorder, how long customers will wait. Kirana Sim models that in TypeScript + Vite: a fixed-timestep game loop at 30 FPS where 90 seconds real-time equals one sim day. Inventory lives on shelves, in fridges, and in the backroom with freshness decay. Suppliers arrive by scooter or truck; customers queue with patience timers; cashiers and stockers have speed, wage, fatigue, and skill attributes loaded from JSON data files.
Challenge
Retail simulation usually means abstract tycoon games—not the specific economics of a neighborhood store where milk spoils, regulars expect staples, and staffing mistakes show up in the day-end P&L.
Solution
Core game engine in src/core/game.ts with data-driven items, suppliers, and random events from JSON. UI modules for HUD, inventory, queue, staff, orders, and day summary; canvas renderer and audio subsystem; Assamese-first i18n via src/locale/i18n.ts because the POC targets Northeast India retail context.
Outcome
Playable kirana simulation for exploring reorder timing, spoilage waste, and staffing trade-offs—research tool for retail ops, not a generic store tycoon clone.
Simulation Systems
Game Loop
- • Fixed-step tick (30 TPS) with rAF render decoupling
- • Day/night progression with pause on hidden tab
- • Customer spawn with budget, patience, and elasticity
- • Checkout flow with cash, reputation, and SFX
- • End-of-day summary: revenue, COGS, spoilage, profit
Data & Localization
- • JSON packs: items, suppliers, cultural events (Bihu, rain)
- • Perishability and shelf-life decay modeling
- • Scooter delivery with ETA and freshness penalty
- • Assamese-first i18n with language selector
- • WebGL1 with graceful fallback if blocked
Key Features
Inventory & Spoilage
Shelf slots, per-item shelf life, decay toasts, and reorder triggers for milk and perishables
Dynamic Pricing
Price sliders with margin hints and demand elasticity—customers abandon if overpriced
Scooter Delivery
Order from mandi suppliers, pay upfront, receive stock after ETA with freshness loss
Assamese-First Experience
Localized HUD, ordering flow, and day summary—designed for regional cultural authenticity
Need a WebGL / game simulation engineer?
Ahmad W Khan built Kirana Sim—a passion R&D WebGL store simulation with TypeScript, fixed-step game loops, i18n, and localized edtech economics modeling. Available for full-time employment, contract, freelance, and consulting on interactive simulations and TypeScript/WebGL products.