Use Cases

Govern the workflows that usually die in review

These workflow pages are built for buyers trying to move from promising AI pilots to governed production. Start with the operational bottleneck, then show how KLA inserts runtime control, human oversight, and exportable execution lineage.

The strongest use-case narratives identify the risky step, show the control point, and make it obvious what reviewers will be able to prove later.

Start the 4-week governed pilot Explore the runtime control plane

Agentic Tool UseHuman Approval EscalationHigh-Risk Enterprise AIShadow AI Guardrails

By Workflow

Featured workflow pages

Each page is written to serve both search intent and buying-committee intent: what is the workflow, where does it break, how does KLA govern it, and what proof gets exported.

Agentic Tool Governance

Agentic Tool Use

Govern AI agents that call APIs, trigger workflows, 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, not by panic: Only the actions that cross a threshold, violate a policy, or touch a sensitive workflow are routed to humans.

Give reviewers enough context to decide: Attach the workflow 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 workflow.

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 workflow 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 workflows 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: The goal is not just to block shadow AI. It is to offer a sanctioned execution path that is safer and easier to adopt.

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Shared Runtime Pattern

What every governed workflow page should prove

Do not lead with a law library, a policy PDF, or a generic governance claim. Lead with the controlled execution path.

Policy-as-code checkpoints

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

Human approval routing

Insert maker-checker review only where the workflow 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 workflow into controlled production without forcing a full stack rewrite.

Workflow Library

Additional workflow patterns

Published pSEO use-case pages stay here as supporting library content. The workflow pages above are the primary public narrative.

No additional published workflow-library pages are visible right now.

KLA

Next step

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

Review your workflow with us

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

Start the governed pilot