Enterprise Knowledge Assistants

An Enterprise Knowledge Assistant is the "Search + Synthesis" engine for a company's internal data. It combines emails, chats, documents, and spreadsheets into a single conversational interface.

Key Challenges

1. Information Silos: Data is spread across Slack, Drive, Jira, and SharePoint.
2. Access Control: Respecting user-level permissions across all those apps.
3. Freshness: Internal docs (like "Meeting Notes") change every hour.

The Architecture Pattern

• Aggregator: A service that periodically scrapes all silos and pushes data to a central S3 bucket.
• Multimodal Index: Since many enterprise docs are screenshots from presentations, OCR and Vision embeddings are critical.
• Semantic Filtering: (Module 12.3) Using department or user_role metadata to gate retrieval.

Impact on Productivity

A well-built Enterprise RAG can reduce the "Time to Find Information" by up to 50%, saving hours of manual searching through Slack threads or nested folders.

Case Study: HR Onboarding

A new employee can ask: "What is our policy on parental leave?"

• The RAG system retrieves the Employee Handbook (PDF), a recent CEO Announcement (Video Transcript), and the Internal FAQ (Markdown).
• It synthesizes a cited response.

Exercises

1. Which data silo at your company would be the most valuable to include in a RAG system?
2. How would you handle a document that is "Privileged" (e.g., between an attorney and a client)?
3. Why is "Context Recency" (preferring 2024 docs over 2019 docs) vital for enterprise settings?