# Tier 3: Data & Knowledge Base (Information Layer)

Tier 3 is the foundational layer that provides the necessary facts, documents, and data required by the higher tiers. It is a passive repository that enables informed reasoning and specialized processing.

## Key Responsibilities

### 1. Information Storage
*   Maintain large-scale repositories of structured data (SQL/NoSQL databases) and unstructured data (PDFs, Markdown files, Codebases).
*   Host internal company documents, project-specific files, and external knowledge graphs.

### 2. Retrieval Mechanisms (RAG)
*   Support efficient querying via Vector Search, keyword indexing, or metadata filtering.
*   Provide Retrieval-Augmented Generation (RAG) capabilities to enrich the prompts of Tier 2 models with relevant snippets.

### 3. Contextual Enrichment
*   Supply specialized models with "ground truth" data to minimize hallucinations.
*   Manage versioned data to ensure the system reflects the most up-to-date information.

## Components
*   **Vector Databases:** (e.g., Pinecone, Milvus, Chroma) for semantic search.
*   **Traditional Databases:** (e.g., PostgreSQL) for structured business data.
*   **File Systems:** Local or cloud storage for direct file access.
*   **External APIs:** Real-time data sources (weather, finance, etc.).

## Interactions
*   Tier 2 specialists query Tier 3 to get the data they need to perform their tasks.
*   Tier 1 may occasionally query Tier 3 directly to determine if sufficient information exists before routing.