Not model monitoring. Not data cataloguing. Governance that spans from source data through model inference through agent action to business decision — every step traceable.
Without governed governance, these problems compound silently with every new data source and AI deployment.
Model monitoring tracks drift but cannot trace decisions through federated data. Oversight is present but incomplete.
AI agents make decisions and invoke other agents — often with no centralised visibility into what data they accessed.
When regulators ask why a credit application was declined, most architectures cannot produce the full chain.
Access controls, PII masking, and lineage enforced at the federation query layer
Bias, drift, and explainability monitored — connected to data lineage below
Permissions, guardrails, and human-in-the-loop gates applied to every agent action
Full reconstruction from source data through model inference to business outcome
Access controls, PII protection, classification, and lineage from the moment data enters the platform.
Bias detection, drift tracking, fairness metrics, and explainability connected to the data layer beneath.
What agents can do, what data they access, what approvals are required — governed by policy, not convention.
The complete audit trail connecting all layers — outcome fairness, full reconstruction, regulator-ready.
See how Tantor's four-layer governance makes every AI decision traceable, explainable, and regulator-ready.