source filtering

**Source filtering** is the **retrieval restriction strategy that allows or blocks results based on origin systems, publishers, or trust tiers** - it enforces data quality and trust controls before evidence reaches generation. **What Is Source filtering?** - **Definition**: Filtering candidates by source identity, provenance score, or approval status. - **Typical Sources**: Internal wikis, ticket systems, vendor manuals, and public knowledge feeds. - **Policy Dimension**: Can enforce allowlists for high-trust content and deny lists for noisy feeds. - **Integration Point**: Applied in retriever query planning and final evidence assembly. **Why Source filtering Matters** - **Evidence Quality**: Trusted sources improve factual consistency and reduce unsupported claims. - **Risk Management**: Blocks low-confidence or unverified origins in high-stakes applications. - **Brand Safety**: Prevents responses from citing disallowed or unofficial content. - **Operational Clarity**: Source-level controls simplify incident response during data quality events. - **User Confidence**: Transparent source policy improves acceptance of AI-generated answers. **How It Is Used in Practice** - **Source Registry**: Maintain central catalog of source IDs, owners, and trust ratings. - **Query-Time Enforcement**: Inject source predicates into retrieval calls using user role and use case. - **Audit Logging**: Record source filters and selected evidence for governance review. Source filtering is **a practical guardrail for trustworthy enterprise RAG** - provenance-aware filtering improves both safety and retrieval signal quality.