GenAI Systems & Integrations

RAG search • Tool-using chatbots (MCP/function calling) • Light tuning • Guardrails & cost control

Proof of capability (live)

SmartDocs — RAG over PDFs: Next.js + LangChain + Jina embeddings + OpenRouter (GPT-3.5) with file/page citations.

RAG architecture: ingestion → chunk/embeddings → retrieval → LLM with citations

What I deliver

  • RAG pipelines: ingestion, chunking, embeddings, retrieval, grounded answers with citations.
  • Chatbots with tools (MCP/function calling) for search, DB queries, internal APIs — demo available on request.
  • Light tuning (LoRA/prompt frameworks) for tone & domain fit, when RAG alone isn’t enough.
  • Safety & quality: guardrails, offline evals, usage budgets, and observability from day one.

Typical stack (options)

  • Models via OpenRouter (OpenAI/Anthropic, etc.) or local (Ollama) where applicable.
  • Vector stores: Pinecone / Weaviate / PgVector — chosen per scale & budget.
  • Next.js or Node services with CI/CD, metrics, and cost governance.

Want reliable AI that ships?

I run short discovery → pilot sprints to land measurable outcomes (better search, faster support, content acceleration), with safety and costs under control.