Service 04 · The studio
RAG pipelines
RAG isn’t ‘add a vector DB.’ It’s an engineering system.
We build retrieval pipelines that are fast, accurate, observable, and continuously improvable. Retrieval-Augmented Generation done right: grounded, cited, and monitored.
Part 01 of 03
What we do
- Data ingestion + cleaning + chunking strategy
- Embeddings + retrieval strategy
- Grounding + citation patterns
- Confidence scoring and safe fallbacks
- Evaluation — answer quality + retrieval quality
Part 02 of 03
When to use RAG
- Internal knowledge base assistants
- SOP and policy Q&A
- Search across docs, tickets, notes, CRM entries
Part 03 of 03
What you get
- End-to-end RAG pipeline
- Dashboard for quality and drift
- Costs + latency tuned for your workload
More · Everything the studio does
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Contact · A useful next step
Work with us.
Ready to talk about RAG pipelines? Tell us what you do, your biggest bottleneck, and what success looks like in numbers.
contact@hime.ai