Documented knowledge infrastructure
VectorHub connects private documents to retrieval-ready AI systems.
A product and API portal for the verified VectorHub stack: Robyn backend, Qdrant vector search, Gel/EdgeDB metadata, document ingestion, chunking and semantic query workflows.
Available
Semantic query API
Experimental
Chunk editor workflows
Planned
Agent SDK/adapters
Verified backend
Robyn API + retrieval services
POST/queryavailable
POST/collectionsavailable
POST/chunk-editorexperimental
GET/ws?token=available
Vector store
Qdrant
Metadata
Gel/EdgeDB
Runtime
Docker
Knowledge flow
1
Ingest
Upload documents and parse source files
2
Structure
Create collections, chunks and metadata
3
Retrieve
Query semantic context through the API
Agent integrations are marked planned until a stable SDK or adapter exists in the repository.
Capabilities
Built from verified repository surfaces
The portal separates implemented capabilities from experimental surfaces and roadmap direction. Claims here are backed by code, compose files or existing project documentation.
Document Ingestion
experimental Transform source material into organized knowledge collections.
Semantic Retrieval
available Retrieve relevant context for applications and agents.
Agent Context
planned Provide contextualized documents to agents and workflows.