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RAG Implementation for Enterprise Knowledge

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Linked challenge: AI-Powered Productivity Agent for Enterprise Cost Optimization

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Linked challenge
AI-Powered Productivity Agent for Enterprise Cost Optimization

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Detail the steps and provide example code for setting up the RAG system that your Mastra AI agent will use. Describe how you would ingest diverse enterprise data (e.g., HR policies, financial reports, operational manuals) into a vector database (like Pinecone or Chroma), generate embeddings, and ensure efficient retrieval. Show how the `rag_retriever` tool would interface with this vector database to fetch contextually relevant information for the agent's analysis.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.