I will fix, debug, or optimize your python rag and vector search pipeline

Facing hallucinations, broken chunking, or slow retrieval in your AI pipeline? I will debug, repair, and optimize your Python RAG architecture.

As an AI integration engineer, I resolve pipeline breakages that cause models to fail in production. Whether your vector index returns irrelevant context or your LangChain execution crashes under concurrency, I provide clean, modular fixes with test cases.

WHAT I FIX:

Vector DB connection, embedding dimension, and indexing mismatches (Pinecone, ChromaDB)

Token chunking errors, sliding-window chunk boundaries, and metadata loss

LangChain and LlamaIndex pipeline exceptions and timeout errors

High latency: optimize similarity search, reranking, and payload caching

HOW WE WORK:

1. Share your code repository or script and sample data.

2. I diagnose the bottleneck and issue a technical triage summary.

3. I deliver the corrected code with clear inline explanations and a test run script.

WHAT IS OUT OF SCOPE:

Greenfield software development and UI design (see my other custom RAG and SaaS gigs).

Message me with your error trace before ordering for a fast assessment.