Data Governance

Every data asset.
Governed from arrival.

Data Governance enforces policy, lineage, access controls, and audit trails across every data asset and every AI agent — from a single governance plane that spans your entire federated estate.

Policy-at-queryAuto-classificationPII maskingEnd-to-end lineageAudit-ready
Data Governance — Active
Access Controls
RBAC + ABAC enforced at query layer
Active
PII Protection
Auto-detected · Masked by role
Protected
Data Lineage
Source to decision — unbroken
Tracking
Data Quality
Validated · Attested · Scored
Passing
Audit Trail
Immutable · Timestamped · Exportable
Recording

Why this matters.
Right now.

Without governed data governance, these problems compound silently with every new data source and AI deployment.

Data governance is disconnected from AI.

Quality rules don't reflect regulatory requirements. Governance policies can't verify whether the data they govern meets the standards they define.

What you can't see, you can't govern.

Assets across federated sources, cloud platforms, and legacy systems are invisible without a governed catalog — ungoverned by default.

Manual enforcement creates gaps.

Per-system governance rules drift apart. The enterprise has no single view of who has access to what across the federated estate.

From input to
governed output.

1

Classify

Auto-classify every data asset — sensitivity, domain, owner, retention requirements

2

Control

Apply access rules — RBAC and ABAC enforced at query time for every identity

3

Protect

PII auto-detected and masked by role before any consumer receives data

4

Track

Full lineage from source through every transformation and agent consumption

5

Audit

Immutable log of every access, policy application, and governance event

What Data Governance
delivers.

📋

Policy enforcement at query.

Access rules enforced at the federation layer — every query governed by the same policy regardless of which tool or agent made the request.

End-to-end lineage.

Trace every data point from source system through federation, governance checkpoints, and agent consumption to the final decision.

🔐

PII auto-detection.

Sensitive fields detected and masked dynamically — by role, context, and consent status — across all federated sources.

Data quality attestation.

Quality rules validated and scored before data reaches agents or reports — quality failures surfaced in the pipeline, not in the boardroom.

See Data Governance
in action.

See how Data Governance works within the Tantor governed intelligence platform.

Frequently asked
questions.

What is data governance?

Data governance is the enforcement of policy, access control, lineage, quality, and PII protection across every data asset — from federated source to AI agent output. Tantor enforces data governance at the query layer, so every access is governed consistently regardless of which tool or agent makes the request.

How does Tantor enforce data governance at query time?

Tantor applies RBAC and ABAC access rules, dynamic PII masking, and quality attestation at the moment data is queried through the federation layer. Policy-at-query means governance is enforced uniformly across all federated sources rather than configured separately per system.

What is the role of data lineage in governance?

Data lineage traces every data point from its source system through federation, governance checkpoints, and agent consumption to the final decision. This unbroken lineage is what lets data governance answer a regulator's question — where did this data come from, who accessed it, and how was it transformed.

Does data governance cover AI agents?

Yes. Tantor's data governance treats AI agents as governed identities with scoped access, the same as human users. Every agent's data consumption is access-controlled, PII-masked, and lineage-tracked, closing the governance gap that ungoverned agent service accounts create.