SortedLaunch.

RAG development

Answers grounded on your data.

A raw model guesses. I connect one to your documents so it answers from what you actually know, with citations you can check. Shipped in weeks, code handed to you.

It cites its sources

Every answer points back to the passage it came from. Your users trust it because they can open the source and read it themselves.

It stops making things up

The model only speaks about what retrieval hands it. When your data has no answer, it says so instead of inventing one.

Live in 2 to 4 weeks

Ingestion, embeddings, retrieval, and a working answer flow. Fixed price, and you know the number before I start.

Retrieval is where RAG lives or dies.

Most RAG that feels dumb has a retrieval problem, not a model problem. I spend the time on chunking, embeddings, and ranking so the right context reaches the model every time. Then I measure it, so we both know it works.

  • Chunking and embeddings tuned to how your content reads
  • Hybrid search and reranking so the best passage wins
  • A test set that scores retrieval, not just vibes

Embeddings

OpenAI or open models, chosen for your accuracy and cost, not for a logo on a slide.

Vector store

pgvector on Postgres when it fits, a dedicated vector database when scale calls for it.

Grounding

Answers built from retrieved passages, with citations and a clear reply when nothing matches.

Handover

Your repo, your keys, your data. The pipeline is documented so your team can extend it.

Where RAG earns its keep.

A few shapes I build most often. We pick the right one together on the call.

Docs and knowledge base

Question answering over your handbook, policies, or product docs, with sources on every reply.

Support assistant

An assistant grounded on your help center and past tickets, so answers stay accurate and on brand.

Internal search

Search across scattered internal data, with permissions respected so people only see what they should.

Point me at your data.

Fifteen minutes on a call and I come back with a scope, a price, and a date. Worst case, you leave with a clearer plan for your RAG.