AI Glossary

Ingest Pipeline

The multi-stage processing system that transforms a raw uploaded file into a fully indexed, searchable asset. Stages include content hashing for deduplication, tool-specific metadata extraction, thumbnail generation, and asynchronous enrichment such as embedding generation and session clustering.

The ingest pipeline is the central architectural component of an AI-native DAM. Every file that enters the system — whether uploaded manually, synced from ComfyUI, or received through an API — passes through the same pipeline stages. This guarantees consistent metadata extraction and indexing regardless of how the file arrived.

The pipeline is designed as a series of stages with increasing cost and latency. Cheap operations (hashing, deduplication, thumbnail generation) run synchronously during upload. Expensive operations (embedding generation, quality scoring, session clustering) run asynchronously in the background, progressively enriching the asset record over minutes rather than blocking the upload for seconds.

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