Agent Data Governance Framework

5-Layer enforcement model for multi-agent workflows

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Layer 1 — Context Graph
Property graph of the complaint → refund workflow. Nodes = entities (agents, tools, data). Edges = data/context flow with constraints.
Layer 2 — Data Tagging
Enterprise data classification register. Every field tagged with sensitivity level — defined once, applies to all workflows.

Field Classification Register

#SourceFieldSensitiveLevelRationaleActions
Layer 3 — Access Control
Per-agent access policies. Each agent has its own access card — expand to view and edit field-level permissions.
Layer 4 — Enforcement
L2 (sensitivity) + L3 (access) = enforcement decision. Five modes determine how each field is handled at runtime.

4 Enforcement Decision Matrix

P Protected Workflow — Enforcement Applied

Same pipeline as Layer 1, now showing what each step actually receives after enforcement.
Layer 5 — Audit Trail
Cryptographic audit log. Every step recorded with hash chain — tamper-evident, regulator-queryable.

5 Audit Log

#TimestampStepAgentActionFields ReceivedL2 TagsL3 AccessL4 EnforcementWhat LLM ReceivedEntry HashPrev Hash

Regulator Query Example

Claim: "RefundBot never saw the merchant's raw UPI ID"
Step 1: Locate audit entry #7 (RefundBot receives handoff payload)
Step 2: Check L3 column — RefundBot access to upi_id = "Verification"
Step 3: Check L4 column — Enforcement = "Compute-and-replace (boolean)"
Step 4: Check "What LLM Received" — upi_id field shows is_valid_upi: true, not the raw value
Step 5: Verify hash chain integrity — each entry hash includes the previous hash
Verdict: Claim verified. RefundBot received a boolean, not the raw UPI ID.
Live Demo
Step through the workflow and watch all 4 governance layers enforce in real time at each step.
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