As agents call tools and trigger workflows, customers need control at the moment of action.
40%+
Gartner predicts over 40% of agentic AI projects will be canceled by 2027 because value and risk controls remain unclear.
80%
SailPoint found 80% of companies say AI agents have taken unintended actions, including unauthorized access or data sharing.
1 in 8
HiddenLayer reports autonomous agents now account for more than 1 in 8 reported AI breaches.
A modular motion for customers moving agentic workflows from pilot to governed production.
Help customers progress from agentic AI experimentation to governed deployment.
Limit broad standing permissions and constrain what agents can do at runtime.
Support architecture validation before customers scale agentic workflows.
Provide proof-of-execution receipts instead of relying only on logs or after-the-fact monitoring.
Give WWT a consultative path for AI security, modernization, and operational readiness conversations.
A value-add for WWT clients: a focused readiness conversation to identify where agents are gaining authority, where execution risk is emerging, and what should be validated before scale.
Which agents or automations are taking action today
Which systems, tools, APIs, or workflows those agents can access
Where agents may have excessive authority
Whether actions are authorized before execution
Whether unauthorized actions fail closed
Whether the organization can prove what happened after execution
Where governance, auditability, or security gaps may slow production deployment
Use these when a customer is exploring agents, tool-calling, or AI-driven workflows that can take action.
Are any of your AI agents allowed to take real action across tools, workflows, APIs, or systems of record?
How are you controlling what an agent is allowed to do at the exact moment it acts?
Are agents using broad credentials, standing permissions, or access scopes that were designed for humans or traditional applications?
What happens if an agent attempts an unauthorized or unverifiable action?
Can you prove which agent acted, under which policy, and why the action was allowed or denied?
Is security, governance, or auditability slowing down your move from AI pilots to production deployment?
When a customer is letting AI agents take action, Crittora gives WWT a runtime control layer to verify authority before execution and produce proof after execution.
Crittora sits where agent intent becomes system execution: verifying authority, failing closed, and producing proof before workflows reach tools, APIs, and systems of record.
The control point sits between the agent and the systems it wants to change.
Initiates action
Verifies authority, enforces policy, fails closed, issues proof
Receives authorized request
Executes only verified actions
Scan the trigger. Expand only the scenarios that match the customer conversation.
“We are building AI agents that can take action.”
WWT opportunity: Help the customer move from experimentation to governed execution.
Crittora role: Enforce runtime authority and generate proof for agent-driven actions.
“Our agents need to call tools or services.”
WWT opportunity: Add governance to the tool execution layer.
Crittora role: Verify permissions before the tool call executes.
“Agents need access to operational systems or sensitive workflows.”
WWT opportunity: Reduce risk around system access and action authority.
Crittora role: Constrain what agents can do and prove what occurred.
“We are using AI to assist with deployment or infrastructure operations.”
WWT opportunity: Support safer automation across cloud and DevSecOps environments.
Crittora role: Enforce action-level permissions before execution.
“We need auditability for AI-assisted decisions or actions.”
WWT opportunity: Support compliance-oriented AI modernization.
Crittora role: Provide verifiable proof-of-execution receipts.
“We need secure AI adoption in a high-trust environment.”
WWT opportunity: Support public sector AI modernization and risk reduction.
Crittora role: Provide fail-closed execution control and proof at the point of action.
Six practical paths for architecture, validation, and customer readiness conversations.
Help customers design governed AI execution patterns.
Add control at the point of action.
Prove the architecture in a testable environment.
Support secure AI movement from pilot to production.
Address security, auditability, and operational risk.
Open consultative customer conversations.
A private set of assets to help WWT teams evaluate Crittora, start internal conversations, and identify customer-fit opportunities.
Deeper guide for WWT sellers, partner managers, and solution teams.
Download BriefStart with one customer, one agentic workflow, and one execution-risk scenario.
Customer is exploring AI agents, MCP/tool-calling, automation, or AI workflows that take action.
WWT and Crittora align on the customer context, risk scenario, and best entry point.
Lead with a consultative readiness conversation rather than a product pitch.
Choose a specific agentic workflow where execution authority, governance, or proof matters.
Use demo, reference architecture, or ATC-style validation to prove the control pattern.
Advance the most relevant use case into pilot, architecture validation, or customer workshop.