I will build a production grade rag platform with llm and API integration

I build production-grade AI systems not tutorials, not demos. Real platforms that handle real workloads.

ContextIQ is a document intelligence platform I built featuring hybrid vector + knowledge graph retrieval (Zilliz + Neo4j), a smart chunk-filtering layer that cut API costs by 70%, and real-time citation tracking across multi-user sessions.

Aris is an AI-powered assistant I developed with full backend architecture, LLM integration, and persistent memory built to handle nuanced, multi-turn conversations at scale.

These aren't concept projects. They're shipped, working products proof that I understand not just how to call an API, but how to architect systems around it.

My specialty is RAG pipelines and LLM integration. I know where basic retrieval breaks down on complex queries, and I know how to build around it whether that's hybrid search, graph-based reasoning, or smart ingestion filtering.

Beyond AI, I build the backend logic that holds everything together: REST APIs with FastAPI or Node.js, authentication, database design, file storage, and session management.

If you need an AI feature bolted onto an existing product or a full platform built from scratch I can deliver both. M