The ontology engine
for enterprise AI
The missing layer between raw data and AI. Velum builds ontologies that power data contracts—whether your data lives in documents or databases.
BY RESEARCHERS FROM
Two paths to semantic infrastructure
From Documents
Unstructured data → Hypergraphs → Contracts
Extract entities from documents with zero-shot NER, discover relationships with LLMs, and build rich hypergraphs automatically.
Self-correcting pipeline ensures ontology conformance. Hypergraphs capture n-ary relationships that traditional graphs can't.
From Databases
Relational sources → Ontology mapping → Contracts
Map existing database schemas to domain ontologies. Align relational sources with your semantic model.
Generate data contracts from ontology definitions. Enforce consistency across federated data products in your data mesh.
Connect any enterprise data source
Velum integrates with your existing enterprise stack—extracting event logs, master data, and transactional records to construct comprehensive operational hypergraphs.
Data extraction capabilities
- Connect in minutes with pre-built extractors.
- Supports SAP, Oracle, Salesforce, ServiceNow, and 50+ enterprise systems.
- Real-time event streaming and batch processing modes.
- SOC 2 Type II certified with enterprise-grade security.
Why ontologies?
Raw data doesn't speak for itself. Ontologies define what your data means—the entities, relationships, and rules that turn information into knowledge. They're the semantic layer that lets systems understand context, enforce consistency, and power intelligent applications across your entire data landscape.
From data to meaning
Ontologies capture what entities are and how they relate—turning raw records into structured knowledge your systems can reason about.
Enforceable consistency
Derive data contracts from ontology definitions. Validate at ingestion, catch drift automatically, govern quality across the mesh.
One language, many sources
Bridge documents, databases, and APIs under a unified semantic model. Same concepts, same meaning, regardless of origin.
Knowledge AI can use
Structured, semantically-rich data that LLMs and agents can query, reason over, and ground their outputs in.