AI & Full-Stack Engineer
Apps, Chatbots, Backend Systems

My Approach

  • Problem First β€” Identify the real user pain before writing code
  • AI as a Tool β€” Use LLMs where they add value, not as a gimmick
  • Production-Ready β€” Every project includes infra, testing, and deployment
  • Open Engineering β€” Document decisions, trade-offs, and failures publicly
AI and Backend Systems Architecture

AI Projects

Production-Ready AI Systems

Not experiments β€” full-stack applications with real infrastructure.

MicroItinerary β€” AI Travel Planner

development

Problem

Travel apps optimize for proximity and ratings. They don't consider human energy levels, group dynamics, or budget constraints intelligently.

Solution

AI-powered PWA that generates personalized annual travel itineraries with intelligent destination suggestions, cost estimation in INR, and Splitwise-style expense splitting.

AI Approach

GPT-4 for destination recommendations based on season, budget, and preferences. AI-generated cost breakdowns for hotels, food, transport, and activities.

Tech Stack

React 18ViteSpring Boot 3.2.2Java 21PostgreSQL 16RedisOpenAI GPT-4
StellarMIND β€” Chat-to-SQL with pgvector screenshot

StellarMIND β€” Chat-to-SQL with pgvector

development

Problem

Business users need to query databases without knowing SQL. Existing tools lack context-aware query generation and safety guarantees.

Solution

Spring Boot MCP server that converts natural language questions into read-only SQL using LLM with retrieval-augmented context from pgvector.

AI Approach

RAG-based SQL generation: schema knowledge stored as embeddings in pgvector, retrieved as context for LLM. Strict read-only enforcement (only SELECT/WITH).

Tech Stack

Spring BootSpring AIPostgreSQLpgvectorMCP ProtocolOpenAI
MyFinancial β€” Personal Financial Advisor screenshot

MyFinancial β€” Personal Financial Advisor

development

Problem

Financial planning in India is fragmented across banks, insurance, and tax documents. Most tools require sharing sensitive data with third parties.

Solution

Privacy-first PWA that consolidates financial data locally via a 6-step wizard β€” Profile, Income, Assets, Liabilities, Insurance, Tax β€” with real-time advisory metrics like Financial Runway and Savings Rate.

AI Approach

Rule-based advisory engine for Indian financial instruments (PPF, EPF, NPS). Old vs. New Tax regime comparison. Coverage gap analysis for insurance. No cloud dependency β€” all computation runs locally.

Tech Stack

React 19Vite 7Tailwind CSS 4ZustandDexie (IndexedDB)Spring Boot 3.xJava 21PostgreSQL
Read full architecture notes β†’
Engineering Quality

Reliability & Production Readiness

πŸ“Š

Observability

Prometheus + Grafana

Production-grade metrics, dashboards, and SLO visibility.

  • RED/USE metrics with custom business KPIs
  • Grafana dashboards for latency, throughput, error rates
  • Alerting and environment-aware scrape configuration
Learn more β†’
⚑

Load Testing

k6

Performance validation for high-throughput, event-driven systems.

  • Scenario-based tests (ramping, soak, constant-arrival-rate)
  • Thresholds on p95/p99 latency and error rates
  • CI-compatible execution and reports
Learn more β†’
πŸ”—

API Contract Testing

Postman + Newman

Repeatable regression and smoke testing for REST APIs.

  • Environment-driven collection execution
  • Newman CLI with HTML/JUnit reports
  • Pipeline-friendly contract validation
Learn more β†’
πŸ“¨

Event-Driven Testing

Kafka Simulation

Deterministic testing of Kafka consumers and workflows.

  • Forked Kafka simulation repos for event replay
  • Partitioning and ordering validation
  • Failure, retry, and backpressure testing
Learn more β†’
Testimonials

What Clients Say

β€œ

Rohit delivered our MVP in 5 weeks β€” on budget and ahead of schedule. His architecture decisions saved us from rewriting everything when we scaled.

Client Name
Founder, Startup Name
MVP Development
β€œ

We needed a WhatsApp bot for our clinic chain. Rohit understood the problem immediately and shipped a working solution that our staff could use without training.

Client Name
CTO, Company Name
WhatsApp Bot
β€œ

What impressed me most was the transparency. GitHub access from day one, weekly demos, no surprises. The React Native app he built is still running with zero issues.

Client Name
Product Manager, Company Name
Mobile App