RAG Development
for
Pharmaceutical & Biotech Companies.

Data audit - assessing the quality, format, and structure of the documents and data to be indexed

Vector database selection - evaluating Pinecone, Weaviate, pgvector, and other stores for your requirements

RAG pipeline build - chunking, embedding, retrieval, and reranking implementation

Evaluation framework - building the accuracy and relevance metrics that prove the RAG system is working

An LLM that answers questions about your data accurately without hallucinating

Query response accuracy above the minimum threshold required for the use case

A retrieval pipeline that stays current as new documents are added without manual reindexing