check point support MMA

MMA_Support/Tier3_Knowledge.md

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+# 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.