RAG System Development
Answers grounded in your knowledge.
Retrieval-augmented generation that turns your documents, wikis, and databases into an accurate answer engine. We design ingestion, retrieval, and evaluation per domain, and measure quality against your own test set before launch.
0%
average answer accuracy
0K+
documents in a single index
0
eval questions per project
01 · What you get
Built in, not billed extra
Domain-tuned ingestion
Chunking, embedding, and indexing strategies chosen for your content type, not copied from a template.
Hybrid retrieval and reranking
Vector search combined with keyword search and rerankers, tuned until the right passage comes back first.
Grounded, cited answers
Every answer links back to its source, so users can verify and trust what the system says.
Evaluation-first quality
We build a 150 to 300 question evaluation set with you and track accuracy on it before and after launch.
02 · How we work
From first call to launch
Audit your knowledge
We inventory your sources: docs, tickets, databases, and decide what belongs in the index.
Build the pipeline
Ingestion, embeddings, retrieval, and generation wired together with your access controls respected.
Evaluate and tune
We iterate against the evaluation set until accuracy meets the bar we agreed on.
Ship with monitoring
Retrieval hit rate, latency, and cost dashboards, plus alerts when knowledge goes stale.
03 · The stack
Tools we reach for
Ready to start?
Tell us what you are building and we will send back a plan and a quote within two business days.