You will get RAG Knowledge Base on Your Docs — Shipped in 2 Weeks
Top Rated
Project details
Get a production-ready RAG pipeline built on your existing documents,
product data, or internal content.
What's included:
— Document ingestion and chunking pipeline (PDF, Notion, web, custom)
— Vector store setup (Pinecone or Supabase Vector) with OpenAI or
Voyage AI embeddings
— Query API with context retrieval and GPT-4o / Claude response layer
— Streaming chat UI built in Next.js
— Deployed to Vercel + Supabase (or your infra)
— Error handling, rate limiting, and basic usage logging
Async-friendly. Fixed price. Clear milestones with written updates.
Scope outside this package (quoted separately): custom auth, multi-tenant
architecture, advanced hybrid search, file upload UI.
product data, or internal content.
What's included:
— Document ingestion and chunking pipeline (PDF, Notion, web, custom)
— Vector store setup (Pinecone or Supabase Vector) with OpenAI or
Voyage AI embeddings
— Query API with context retrieval and GPT-4o / Claude response layer
— Streaming chat UI built in Next.js
— Deployed to Vercel + Supabase (or your infra)
— Error handling, rate limiting, and basic usage logging
Async-friendly. Fixed price. Clear milestones with written updates.
Scope outside this package (quoted separately): custom auth, multi-tenant
architecture, advanced hybrid search, file upload UI.
Programming Languages
HTML & CSS, Python, TypeScriptCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included $1,000
These options are included with the project scope.
$1,000
- Delivery Time 16 days
- Number of Revisions 1
- Design Customization
- Content Upload
- Responsive Design
- Source Code
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Sushant C.
May 30, 2026
Full Stack AI (MERN Stack) developer needed for development of new Gen AI / Agentic AI Features
Excellent work on AI integration and agentic AI implementation. Delivered a well-structured, scalable solution with strong technical expertise in LLMs, AI agents, and automation workflows. Communicated clearly throughout the project, met deadlines, and went the extra mile to ensure everything worked as expected. Highly recommend for any AI/ML or agentic AI project.
YD
Yedidya D.
May 12, 2026
Shopify app dev
integrate amazing and very good at finding new solutions - we are very happy to choose him as our developer
Sumit made us so much order in the software - it worth alot!
very good guy
Sumit made us so much order in the software - it worth alot!
very good guy
YD
Yedidya D.
Nov 18, 2025
Shopify app dev
About Sumit
AI-Integrated Full-Stack Engineer | Next.js, RAG, LLM | Top Rated
100%
Job Success
Jammu, India - 2:33 am local time
I build production-ready AI features and SaaS backends — RAG pipelines, LLM integrations, async event systems — and I fix the performance and accuracy issues that show up when they hit real traffic.
Top Rated · 100% Job Success Score · Fixed-price or hourly · Async-first.
——
WHAT I BUILD
→ RAG knowledge bases and LLM integration — GPT, Claude, Voyage AI, Pinecone, Supabase Vector, OpenAI embeddings
→ AI-powered internal tools, CRMs, and agentic workflow automation
→ Full-stack SaaS — Next.js, React, Node.js, NestJS, TypeScript, Supabase, PostgreSQL, Python, FastAPI, Redis
→ Async event and queue systems — BullMQ, Inngest — idempotent, high-volume data workflows
→ Performance engineering — latency profiling, PM2 cluster mode,core web vitals
→ Secure, resilient deployments — Docker, Vercel, Cloudflare, Netlify, Railway, AWS, Hetzner, DigitalOcean — environment hardening, secrets management, and zero-downtime releases
——
A FEW THINGS I'VE SHIPPED
Falcon CRO — Shopify behavioral analytics (Node.js, Redis, BullMQ, React)
The server was throttling and dropping payment events during sales spikes.
I rebuilt the async processing layer with BullMQ, implemented idempotent
event and payment handling, and configured PM2 cluster mode for horizontal
scaling. P50/P90 latency improved 3× and core web vitals improved 8× for
their Shopify App Store submission.
SFMC Studio — Salesforce analytics platform (Next.js, MongoDB, AWS EC2)
Inaccurate metrics and slow aggregation pipelines were causing reporting
errors downstream for enterprise clients. I rebuilt the Salesforce Cloud
data ingestion with queue-based processing for safe, accurate delivery to
MongoDB and restructured the aggregation layer. Metrics accuracy improved
5× and web vitals improved 2–3×.
Custom AI-Powered CRM — Lending business, Irvine CA
(GPT-4o, NestJS, Aircall, Twilio, Zillow API, PostgreSQL, Azure)
Started on frontend, grew to full-stack ownership. Shipped modules for
AI-assisted lead management, Aircall call integration, Zillow property
enrichment, webhook processing, and Google Calendar + Outlook sync.
Lexilift AI — My own RAG SaaS
(Supabase, Pinecone, Voyage AI, GPT-4o, Claude Sonnet 3.5, Next.js)
Designed and built the full ingestion and query pipeline from scratch —
document chunking, vector embedding, context retrieval, and streaming
query API — for a multi-domain business knowledge base.
——
WHAT A RECENT CLIENT SAID
"Excellent work on AI integration and agentic AI implementation. Delivered a well-structured, scalable solution with strong technical expertise in LLMs, AI agents, and automation workflows. Communicated clearly throughout, met deadlines, and went the extra mile. Highly recommend for any AI or agentic AI project."
——
HOW I WORK
Fixed-price with a clear scope document, or hourly for ongoing builds.
Async-first — no mandatory standups, clear written updates, and I flag blockers before they become delays.
If you have a project, send a message with a brief scope and I'll tell you honestly whether I'm the right fit.
Steps for completing your project
After purchasing the project, send requirements so Sumit can start the project.
Delivery time starts when Sumit receives requirements from you.
Sumit works on your project following the steps below.
Revisions may occur after the delivery date.
Assess -> Review -> Design -> Develop -> Test -> Deploy -> Deliver