Custom AI RAG Systems
Chat with your data. Secure, small-to-mid scale knowledge bases powered by vector search and LLMs.
RAG systems that let your team or customers query documents in natural language. We implement vector databases, embeddings, and secure access so you get "chat with your data" without exposing sensitive content.
- "Chat with your data" interfaces
- Vector databases & embeddings
- Secure knowledge bases for docs
FAQs
What does a minimal RAG system include?
Ingestion, chunking, embeddings, retrieval, prompting, and evaluation hooks—plus access control so the model only sees allowed documents.
How do you reduce hallucinations?
Grounding prompts, citation patterns where appropriate, retrieval quality work, and human review for sensitive answers.
Can it run on our VPC or private cloud?
Often yes, depending on model hosting choices. Constraints are mapped early so architecture is not an afterthought.
How long does a first useful version take?
Depends on corpus quality and evaluation criteria; a focused pilot can be weeks, while broad knowledge bases take longer to harden.