Specialised · under AI Development

RAG System Development Services

Most RAG demos retrieve well but generate badly. We build production RAG with hybrid retrieval, evaluation harnesses, source citations, hallucination guardrails and cost-aware generation.

What we build

What you receive

Why custom over off-the-shelf

Most RAGs are mostly retrieval

The retrieval step is what makes or breaks the answer. Pure vector search alone is not enough — hybrid retrieval + reranking typically lifts quality 20-30%.

Evaluator harnesses are mandatory

Without a golden Q&A set and regression evals, you can't tell when prompt or model changes broke things. We build the evaluator first.

Pricing and timeline

Price range

$30,000 – $90,000

USD, fixed-cost after written scope

Timeline

10 – 14 weeks

From kickoff to production

FAQ

pgvector or a dedicated vector DB?

For most teams, pgvector on a Postgres instance you already operate beats a separate vector DB until scale forces a split. Avoid premature operational complexity.

How do we evaluate RAG quality?

Golden Q&A datasets, retrieval-quality metrics (precision@k, recall@k), generation evaluators (LLM-as-judge with rubric, human eval where stakes are high).

Related specialised services

Ready to scope this?

Fixed-cost proposal and delivery plan within 48 hours of a 30-minute discovery call.

Get a proposal