Traditional keyword search fails across multiple content repositories, creating a need for a unified, semantic, and permission-aware solution.
The Hyland AI Ready Hub is an open-source, on-premise platform for building a multi-source, permission-aware RAG system to ensure data sovereignty.
The hub sits between knowledge enrichment and discovery, using batch and live ingesters to pull data from sources like Alfresco and Nuxeo into a central RAG service.
Developers can integrate new repositories by implementing four key interfaces for document representation, API communication, text extraction, and content scoping.
The idempotent ingestion process first synchronizes metadata and permissions, then uses a transformation queue for asynchronous text extraction and chunking.
Retrieval accuracy is improved by using asymmetric embedding models for queries versus documents and by combining semantic vector search with traditional BM25 keyword search.
The RAG pipeline processes user queries through hybrid search to build a context-rich prompt for an LLM, providing streaming answers with citations that link back to the original documents.
A live demonstration showcases the unified search and chat interface querying both Alfresco and Nuxeo repositories simultaneously while respecting user permissions.
The entire system is deployed via a Docker Compose stack of over 20 services, with recommendations for GPU-accelerated hardware and options for CPU-only development.
The solution provides AI-powered search without data migration or permission model changes by using key patterns like storage-layer permissions and asymmetric embeddings.
The future roadmap includes support for full on-premise, hybrid, and full-cloud deployments to provide maximum flexibility for enterprise needs.
Jobs that call for the skills explored in this talk.