Agent governanceMortgage & Lending
Govern underwriting agents with policy checks and human review on high-impact lending decisions.
Control focus
Underwriting authority & exceptions
Agent Command Center
Every agent. A governed boundary.
Govern what AI agents can do.
Control which tools agents can use, which actions they can take, and when a human must decide — with a full evidence trail for every decision.
- Agent governance
- Human oversight
- Policy enforcement
- Tool controls
See an agent in action
From business request to controlled action.
Follow a mortgage underwriting example as an AI agent moves from a customer request to a governed business action — with policy enforcement at every step.
Step 1
Customer Request
A mortgage applicant submits a refinance request.
Step 2
AI Agent
The underwriting agent gathers data and prepares a decision.
Step 3
Command Center
CognitiveView evaluates the action against policy.
Step 4
Human Review
High-risk decisions route to an underwriter for approval.
Step 5
Business Action
Approved decision is executed and fully logged.
The new agent reality
Agents don't just answer. They act.
Agents can call tools, access sensitive data, and trigger business decisions. A useful answer is no longer enough: every action needs a clear boundary.
Governance belongs before execution.
Six boundaries. One control layer.
Select a controlIllustrative agent workflow
Identity control01 / Requested action
An underwriting agent requests access to a loan application.
02 / Policy check
Verify the registered agent, its service identity, and its accountable owner.
Allowed
The registered identity is verified before the request proceeds.
Evidence retained
Agent identity, owner, verification result, and request timestamp.
The same boundary follows the agent from request to outcome.
EvaluateEnforceRecord
Agent command center
One record. Full visibility.
Bring every agent into view. Connect who it is, what it can do, and how its decisions are governed — from one control plane.
A record you can trust
Register each agent’s identity, business purpose, and accountable owner in one place.
Permissions with a purpose
Define the tools, data, and actions each agent may use. Keep authority aligned to its assigned task.
Decisions you can explain
Allow, review, or block actions before execution. Route risky decisions to people and retain the evidence behind every outcome.
Know every agent.
Connect identity, purpose, and ownership in one accountable record.
Runtime control
Control at the moment of action.
Policies become actionable boundaries. Evaluate what an agent is about to do, then allow it, pause for human review, or stop it before execution.
Enforce the boundary
Check identity, tools, data access, and action scope against policy before execution.
Keep people in control
Pause high-impact decisions and exceptions for an authorized human reviewer.
Keep the reasoning
Retain the policy, context, decision, and outcome so every action can be explained.
Runtime decision flow
One action. A clear decision.
Explore an illustrative policy scenario.
Agent action
Policy check
Decision
Approved tool call
Update the assigned application record
A registered underwriting agent submits a summary to the approved internal case system.
- 01Verified agent identity
- 02Approved tool and destination
- 03Action within assigned scope
Allow before execution
The action is within policy. The update can proceed to the approved destination.
Evidence retained
Agent identity, tool call, matched policy version, and execution result.
Lifecycle assurance
Governed from registration to retirement.
Identity, policy, assurance, and certification stay connected as an agent moves from onboarding into live operation.
Scroll to follow the agent lifecycle
Command Center / ControlAI Assurance / EvaluateAgent Certification / Certify
- Control
01Register
Give every agent a verified identity, a business purpose, and an accountable owner.
Retained through the lifecycle
Identity & ownership record
- Control
02Assess
Understand the agent’s risk, delegated authority, and required tools and data.
Retained through the lifecycle
Risk & access profile
- Control
03Govern
Attach policies that define what may proceed, what needs review, and what must stop.
Retained through the lifecycle
Runtime policy boundary
- Evaluate
04Assure
Evaluate behavior and control effectiveness in the intended business context.
Retained through the lifecycle
Evaluation & assurance evidence
- Certify
05Authorize
Establish certification for a specific business use, with clear conditions and limits.
Retained through the lifecycle
Scoped authorization
- Certify
06Monitor
Observe live actions and revisit authorization when behavior, context, or policy changes.
Retained through the lifecycle
Monitoring & re-certification trail
When an agent’s scope or behavior changes, its controls and authorization must be revisited.
View the LifecycleUse cases
Built for the agents you run today.
Different industries. Different decisions. Apply the right boundaries to the tools, data, and actions your agents use every day.
Explore all use cases- Agent governance
Agent governanceFinancial Operations
Control agents that initiate payments, reconcile accounts, and prepare financial reports.
Control focus
Payment permissions & approvals
Agent governanceHealthcare
Keep patient-facing agents within defined privacy boundaries and clinical policy.
Control focus
Patient data & clinical oversight
Agent governanceCustomer Service
Keep support agents within approved responses, refund limits, and escalation paths.
Control focus
Refund limits & escalation rules
Agent governanceHR & Recruiting
Apply consistent controls to agents that screen candidates and support hiring decisions.
Control focus
Screening policy & human review
Agent governanceEnterprise Operations
Govern agents that move data and execute workflows across connected business systems.
Control focus
Tool access & workflow boundaries
One governance approach, adapted to each agent’s business context.
Connect your agent ecosystem
Your entire stack. One governance layer.
Models reason. Agents orchestrate. Tools act. Bring the context together so every consequential action has clear boundaries, accountable oversight, and evidence you can explain.
Explore the connection layers
Model inputs move through a structured reasoning pipeline into a reviewed output.
Connection context
Agent intelligence
AI models
OpenAIAnthropicAzure OpenAI
LLMs
GPTClaudeLlama
01Connect the context
Bring model interactions into the context of the agent, its purpose, and the workflow it serves.
02Govern the action
Apply boundaries around sensitive inputs, permitted model usage, and the outputs that need human review.
03Retain the evidence
Keep the model context, applicable policy, and review outcome together so a decision can be explained later.
Business value
Move beyond experiments. Act with confidence.
Give teams the visibility to understand agents, the controls to guide their actions, and the evidence to expand adoption with confidence.
Connect every agent to its purpose, accountable owner, and current risk posture. Give teams a shared starting point for oversight.
For platform and governance teams
Governance in practice01
From
Agents spread across disconnected workflows
With Agent Command Center
A shared registry with clear accountability
Evidence behind the outcome
Agent identity · Owner · Risk context
Clear ownership. Controlled action. Connected evidence.
From possibility to governed action
Give every AI agent a governed boundary.
Deploy agents with confidence. Bring policy, human oversight, and connected evidence to the actions that matter.
- Register agents in minutes
- Enforce policy at runtime
- Prove control with evidence
