real-time indexing

**Real-time indexing** is the **indexing architecture that incorporates source changes into searchable indexes with very low delay** - it supports near-live retrieval for dynamic operational environments. **What Is Real-time indexing?** - **Definition**: Continuous or event-driven indexing that minimizes source-to-search latency. - **Input Stream**: Uses CDC logs, event buses, or webhook triggers for update capture. - **Processing Path**: Runs parsing, chunking, embedding, and write operations in low-latency pipelines. - **Serving Model**: Indexes expose new content quickly while maintaining query availability. **Why Real-time indexing Matters** - **Freshness Targets**: Essential for domains where information validity changes hourly or faster. - **Operational Responsiveness**: Teams can query current state without waiting for nightly rebuilds. - **Incident Handling**: Urgent updates become searchable almost immediately. - **Trust and Adoption**: Users rely on AI more when it reflects live system reality. - **Competitive Speed**: Fast knowledge propagation improves organizational reaction time. **How It Is Used in Practice** - **Event-Driven Pipeline**: Process source-change events with idempotent indexing jobs. - **Dual-Write Safeguards**: Maintain atomic metadata and content updates to prevent partial visibility. - **Latency SLOs**: Track source-to-index delay and alert on threshold violations. Real-time indexing is **a key enabler for low-lag RAG knowledge delivery** - with robust streaming pipelines, real-time indexing keeps retrieval aligned with current data.