Inferal
Data infrastructure / operational intelligence platform
A data infrastructure platform that sits on top of a company's existing databases and message queues and turns them into an event-driven substrate for AI agents. It keeps live operational models of entities, relationships, policies and rules in sync with data at rest and data in motion, evaluates declared business rules continuously, and activates agents with the relevant context when conditions are satisfied.
- Continuous condition matching that activates agents when rules are satisfied, removing the need to poll
- Operational models of entities, relationships, policies and rules kept in sync with source systems
- Ontology-based semantic layer so facts, rules and agents share explicit definitions, including competing definitions of the same concept
- Full audit trails and implication graphs making every decision traceable and every consequence explainable
- Connectors to existing databases and message queues covering both data at rest and data in motion, with no stale cache
- Temporal rules that fire at the relevant time boundary rather than on a daily batch
- Git-based workspace with MCP servers for integration
Built for
Enterprise data and engineering teams deploying AI agents in decision-critical operations, concentrated in financial services (fraud detection, AML), risk and compliance, and logistics and supply chain, with stated applicability to healthcare and biotech, e-commerce, manufacturing, energy and utilities, and telecommunications.