Use Cases

Govern the Processes that usually die in review

Move your AI Processes from promising pilots into governed production. KLA inserts runtime control at the risky step, routes human oversight where it matters, and exports signed execution lineage your reviewers can verify.

Each use case below identifies the step that usually fails review, the control point KLA enforces, and the proof you can hand an auditor afterward.

Agentic Tool UseHuman Approval EscalationHigh-Risk Enterprise AIShadow AI Guardrails

By Process

Featured Processes

For each one: what the Process is, where it breaks, how KLA governs it, and what proof gets exported.

Agentic Tool Governance

Agentic Tool Use

Govern AI agents that call APIs, trigger Processes, or move data. Add runtime checkpoints, approvals, and signed execution lineage before side effects happen.

Intercept tool calls in flight: Evaluate API calls, system writes, and outbound actions before the agent reaches the target system.

Escalate only the risky cases: Low-risk actions keep moving while high-impact side effects route to named reviewers with context.

Export proof of every side effect: Keep signed records of the policy hit, reviewer identity, action payload, and downstream response.

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Human-in-the-Loop Control

Human Approval Escalation

Add human approval escalation to high-stakes AI decisions. Route the right cases to named reviewers with full context, policy hits, and replayable execution lineage.

Escalate by policy: Only actions that cross a threshold, violate a policy, or touch a sensitive Process are routed to humans.

Give reviewers enough context to decide: Attach the Process state, tool payload, supporting evidence, and recommended action in the approval request.

Keep the approval record attached to the run: Every approval, rejection, reassignment, and note is preserved as part of the signed execution lineage.

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High-Risk AI Governance

High-Risk Enterprise AI

Control high-risk enterprise AI in finance, insurance, healthcare, and government with runtime checkpoints, human oversight, and provable execution lineage.

Turn control requirements into runtime checkpoints: Move from policy documents and review committees to actual decision-time controls that sit in the live Process.

Combine automation with accountable human oversight: Only the risky steps are paused, and every human intervention is preserved in the same execution chain.

Export proof for internal and external review: Capture the technical trace and the governance trace together so reviewers can see how the Process was controlled.

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Shadow AI Controls

Shadow AI Guardrails

Bring unmanaged AI use into a governed execution path. Discover risky actions, enforce guardrails, and export proof of approvals, policy hits, and downstream effects.

Move from discovery to governed adoption: Use incidents and near misses as a map for where runtime controls are actually needed, then wrap those Processes first.

Control data movement and system actions: Focus on the operational boundary where unmanaged AI touches records, systems, or external tools.

Create a path that teams will use: Offer a sanctioned execution path that is safer and easier to adopt than the unmanaged one.

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Shared Runtime Pattern

What every governed Process gives you

A controlled execution path you can put into production: policy checkpoints, human approval routing, signed lineage, and an adoption path that fits your stack.

Policy-as-code checkpoints

Evaluate tool calls, thresholds, sensitive data, and Process state before the action executes.

Human approval routing

Insert maker-checker review only where the Process actually needs a named human decision.

Execution lineage

Keep a signed record of prompts, policy hits, approvals, downstream actions, and final outcomes.

Production adoption path

Move one high-stakes Process into controlled production without forcing a full stack rewrite.

KLA

Next step

Want help mapping one Process to checkpoints, approvals, and signed execution lineage?

Review your Process with us

We can propose the runtime checkpoints, human approval path, and evidence export you need to move it into production safely.