Eppa Akhiranandhan Reddy

Your AI prototype works in the demo, then breaks the moment real users hit it. I build the version that doesn't, production RAG pipelines, LLM agents, and full-stack AI apps that survive real load.
For the last 3 years I've been the sole engineer behind several live AI platforms, including a HIPAA-adjacent healthcare AI platform serving real patients globally (RAG chatbot, provider matching, programmatic SEO, Stripe payments) and a production RAG system that processes government RFPs end-to-end with OCR ingestion, vector retrieval, and structured LLM output.
What I build:

• Production RAG systems — document ingestion, OCR, embeddings, pgvector/ChromaDB retrieval, hallucination control, source citations

• AI agents & multi-agent orchestration, LangGraph/LangChain, tool calling, human-in-the-loop

• Full-stack AI apps; Next.js + FastAPI, auth, billing, dashboards, multi-tenant

• Cloud deployment; AWS (Bedrock, ECS, S3, RDS) and GCP (Cloud Run, Document AI), Docker, CI/CD
How I work: I own projects end-to-end, architecture, build, deploy, and support. I ship fast without cutting corners on reliability, and communicate clearly throughout.
Stack: Python, TypeScript, FastAPI, Next.js, React, LangChain, LangGraph, OpenAI & Anthropic Claude APIs, AWS Bedrock, pgvector, ChromaDB, PostgreSQL, Supabase, Redis, Docker.
My client repos are private/client-owned, but I'll happily give you a live demo, a walkthrough, or screen-share the actual production systems on a call.
If you're building an AI product, adding an LLM/RAG layer to an existing app, or need an AI agent that works in production, tell me what you're building and I'll tell you exactly how I'd approach it.