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Rohit Raj
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Un founding engineer indien qui livre de bout en bout sur n'importe quelle stack — IA, backend, mobile, blockchain, iOS, web3 — sans le coût d'une équipe.

Lancez votre MVP IA en 6 semaines.
29 produits livrés, tous documentés.

Sprint MVP 6 semaines · 50 % remboursés si on manque le jalon de la semaine 3
Réserver un appel gratuit de 30 minProjets IAEngineering Notes
  • Prix fixe · Aucune surprise horaire
  • Vous possédez le code · MIT ou commercial
  • Accès quotidien Slack / WhatsApp
  • Premier commit en production en 5 jours
AI and Backend Systems Architecture
Projets IA

Systèmes IA Prêts pour Production

Pas des expériences — des applications full-stack avec une vraie infrastructure.

01

MicroItinerary — AI Travel Planner

liveSource

Problème

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.

Approche IA

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

Build time
6 weeks
GPT-4 cost / itinerary
<$0.08
PWA Lighthouse
94/100
React 18ViteSpring Boot 3.2.2Java 21PostgreSQL 16RedisOpenAI GPT-4
02

StellarMIND — Chat-to-SQL with pgvector

liveSource
StellarMIND — Chat-to-SQL with pgvector

Problème

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.

Approche IA

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

Query latency p95
<1.2s
SQL safety
100% read-only
Schema embeddings
pgvector
Spring BootSpring AIPostgreSQLpgvectorMCP ProtocolOpenAI
03

MyFinancial — Personal Financial Advisor

liveLiveSource
MyFinancial — Personal Financial Advisor

Problème

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 — Profile, Income, Assets, Liabilities, Insurance, Tax — with real-time advisory metrics like Financial Runway and Savings Rate.

Approche IA

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 — all computation runs locally.

Data privacy
100% on-device
Wizard completion
6 steps · ~4 min
Tax regimes covered
Old + New
React 19Vite 7Tailwind CSS 4ZustandDexie (IndexedDB)Spring Boot 3.xJava 21PostgreSQL
Lire les Notes d'Ingénierie → →
Process

How a 6-week MVP sprint works

Fixed scope. Daily Slack. First production commit by day 5.

  1. 01
    Week 1

    Discovery & architecture

    • Problem framing call
    • Architecture doc
    • Tech stack lock-in
  2. 02
    Week 2

    Core backend & auth

    • Database schema
    • Auth flow
    • First production deploy on day 5
  3. 03
    Week 3

    AI / data layer

    • LLM integration
    • Vector store + retrieval
    • Cost guardrails
  4. 04
    Week 4

    Frontend & UX

    • UI flows
    • Mobile responsive
    • Analytics events
  5. 05
    Week 5

    Hardening

    • Load tests
    • Observability
    • Security pass
  6. 06
    Week 6

    Launch

    • Bug bash
    • Public deploy
    • Code handover + docs
Qualité Ingénierie

Fiabilité & Préparation Production

📊

Observabilité

Prometheus + Grafana

Métriques, tableaux de bord et visibilité SLO de qualité production.

  • Métriques RED/USE avec KPIs métier personnalisés
  • Tableaux de bord Grafana pour latence, débit, taux d'erreur
  • Alertes et configuration de scraping adaptée à l'environnement
En savoir plus →
⚡

Tests de Charge

k6

Validation des performances pour systèmes event-driven à haut débit.

  • Tests par scénarios (ramping, soak, constant-arrival-rate)
  • Seuils sur latence p95/p99 et taux d'erreur
  • Exécution et rapports compatibles CI
En savoir plus →
🔗

Tests de Contrat API

Postman + Newman

Tests de régression et smoke reproductibles pour APIs REST.

  • Exécution de collections pilotée par environnement
  • Newman CLI avec rapports HTML/JUnit
  • Validation de contrat compatible pipeline
En savoir plus →
📨

Tests Event-Driven

Simulation Kafka

Tests déterministes des consommateurs Kafka et workflows.

  • Repos de simulation Kafka forkés pour replay d'événements
  • Validation du partitionnement et de l'ordre
  • Tests de failure, retry et backpressure
En savoir plus →
Testimonials

What Clients Say

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

Arjun Kapoor
Founder, NovaByte Labs
MVP Development

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.

Priya Mehta
CTO, MediConnect Health
WhatsApp Bot

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.

Vikram Desai
Product Manager, FinLeap Technologies
Mobile App
FAQ

Common questions before we start

What if 6 weeks slips?

Fixed scope means we descope features, not extend timeline.

Who owns the code?

You. Full repo handover on week 6.

Am I locked into your tech stack?

No. I'll ship in your stack if your team has one.

Refund policy?

50% back if we miss the week-3 production deploy milestone.

Rohit Raj — Ingénieur Backend & Systèmes IA

Services

Mobile App DevelopmentAI Chatbot DevelopmentFull-Stack Development

Recevoir les Mises à Jour