Case Study 01

Enterprise AI Copilot.

RAG-powered copilot for knowledge retrieval, document summarization, Q&A, vector search, and agent workflows across large internal document collections.

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copilot_pipeline.yaml

User question
  → FastAPI gateway
  → LangGraph router
  → Retriever + tool calls
  → Vector DB context
  → LLM answer
  → Validation + monitoring

Architecture

Grounded, observable, production-ready.

Ingest

Process internal documents and prepare retrieval-ready chunks.

Embed

Create searchable representations for semantic retrieval.

Retrieve

Rank and validate context before generation.

Orchestrate

Route steps with LangGraph and controlled tool use.

Serve

Expose workflows through FastAPI and cloud services.

Monitor

Track latency, accuracy, hallucination rate, and reliability.

Impact

Reported outcomes

Better answers, faster retrieval.

100K+ documents750K+ monthly requests35% accuracy gain28% fewer hallucinations

Stack

AI engineering

Python, LangChain, LangGraph, FastAPI, FAISS, cloud AI.

Designed as an enterprise AI application, not a demo chatbot.