Accurate AI search grounded in company data
Contact NowRAG (Retrieval-Augmented Generation)
Ground LLM answers in your internal documents and datasets with citation accuracy.
We build vector retrieval pipelines over your internal knowledge bases, technical manuals, and policy documents so AI models answer accurately from your real data without hallucination.
Typical fits
Enterprise knowledge repositories and internal documentation search
Customer support helpdesks needing instant verified document retrieval
Legal, compliance, and medical policy search engines
How we deliver
- 01
Design document parsing, chunking, and metadata tagging pipeline
- 02
Configure vector embeddings and high-performance vector databases (pgvector/Pinecone)
- 03
Implement hybrid lexical & vector search with reranking algorithms
- 04
Synthesize answers with direct inline source document citations
- 05
Evaluate retrieval precision against real employee user queries
Stack
LangChainpgvectorPineconeClaudePython
