02

RAG & knowledge assistants

Make scattered company knowledge searchable, cited, and useful.

Discuss this project ↗

We build retrieval systems that ingest real business content, respect permissions, return source-grounded answers, and improve through evaluation rather than guesswork.

OutcomeFaster answers from trusted sources without asking teams to hunt through folders and threads.

  • ✓Document and knowledge-base ingestion
  • ✓Semantic search and cited answers
  • ✓Internal copilots for teams
  • ✓Permission-aware retrieval
  • ✓RAG debugging, evaluation, and cost tuning
  • ✓Ingestion and chunking pipeline
  • ✓Embedding and retrieval strategy
  • ✓Vector database implementation
  • ✓Citations and source links
  • ✓Evaluation set, monitoring, and documentation
LangChainLlamaIndexPineconeQdrantpgvectorOpenAIAnthropic
Next capabilityAI chatbot development→

Let's turn the hard part into your advantage.

Tell us what you are building, what is blocked, and what success looks like.

Start a conversation ↗