Querying with HXQL
Search, filter, count, and aggregate Cloud Content Repository documents with HXQL, including ingest properties, context properties, and knowledge graph processing states.
Semantic and Hybrid Search
Find the most relevant content chunks with vector (k-NN) search over Cloud Content Repository embeddings, combine it with full-text matching, and look up individual embeddings.
Downloading Content
Download document binaries from the Cloud Content Repository, either streamed through the API or through a temporary pre-signed URL, with range, conditional and digest requests.
Setting Up the Knowledge Graph
Create a graph database, upload an ontology, and route documents to it with ontology route conditions, then verify the configuration and clean up safely.
Working with Graph Data
Retrieve Business Objects, related Business Objects, shared attributes and provenance from a knowledge graph, and group its entities with aggregate queries.
Rebuilding the Graph
Run graph rebuild jobs to apply ontology routes to existing Cloud Content Repository documents and re-trigger knowledge graph processing, scoped to one graph database.