Project 04: Enterprise RAG Platform

Objective

Build a knowledge assistant that retrieves documents, constructs grounded context, answers with citations, enforces access control, and evaluates retrieval and answer quality.

Capabilities

• Document ingestion.
• Semantic search.
• Hybrid search.
• Citations.
• Metadata filtering.
• Access control.
• Multi-tenant isolation.
• Conversation history.
• Feedback.
• Evaluation.
• Audit logs.

Architecture

User -> Web/API -> Auth/RBAC -> Query Understanding -> Keyword Search + Vector Search -> Reranker -> Context Builder -> LLM -> Answer + Citations

Tasks

• Create ingestion pipeline.
• Add document parsing.
• Add chunking and metadata.
• Store embeddings.
• Implement vector search.
• Implement hybrid search.
• Add reranking.
• Add citation formatting.
• Enforce document permissions.
• Add evaluation dataset.
• Create evaluation report.

Evaluation Dataset Columns

• Question.
• Expected answer.
• Expected source.
• Actual answer.
• Retrieved sources.
• Score.
• Notes.

Tips

• Evaluate retrieval before tuning prompts.
• Keep source references traceable to original documents.
• Add permission filters before retrieval results reach the LLM.
• Track failed questions as regression tests.