Advanced
Developer Tools
AI Infrastructure
Knowledge Management
Build a RAG Knowledge Assistant Like an Enterprise AI Team
Stand up a working retrieval-augmented assistant over your own documents in about half a day.
Time Required
Half a day, one-time setup
Expected Result
A working assistant you can query in natural language that answers using your own document set as its source of truth.
1
Collect Your Documents and Knowledge Base
Gather every document, wiki page, or file you want the assistant to be able to reference and answer questions from.
2
Chunk and Embed Into a Vector Database
Use Pinecone to store vector embeddings of your documents so they can be retrieved by semantic similarity.
Pinecone
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3
Wire Up a Retrieval Chain
Build the retrieval and prompt logic in LangChain so queries pull the right document chunks before generating an answer.
LangChain
4
Query It Like an Internal Expert
Start asking the assistant natural-language questions and refine the retrieval logic based on how well it answers.
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