Assess your AI controls. Discover what is really in use. Turn evidence into a risk-based roadmap for the AI you build and consume — with the Ascendra AI Clarity Framework.
Get an executive view of your AI runtime readiness. Answer 10 practical questions, see where gaps may exist and leave with three clear next steps.
Check my AI readinessBring your control environment and actual AI use into one conversation. Turn what we learn into a practical, risk-based roadmap for the AI you build and consume.
Assess applicable security controls against MITRE SAFE-AI, complemented by governance criteria. Establish what is documented, implemented and supported by evidence.
Discover approved and shadow AI across the agreed scope. Identify applications, models, agents, connectors, data exposure and activity. Make coverage limits visible.
Combine context and evidence. Assess use-case risk, select proportionate controls and define the path toward an AI control plane.
Understand the capabilities behind responsible AI adoption. Explore each dimension to see the question it answers and the evidence behind it.
Establish the AI footprint: applications, embedded AI, models, agents and connections. Reconcile what is approved with what is observed, and make remaining blind spots explicit.
EVIDENCE TO EXAMINEInventory records, named owners, discovery coverage, data flows and agent or tool activity.
Explore the full frameworkPurchased tools and embedded features. Assess intended use, information shared, integrations, reliance on outputs and the split between supplier and customer responsibilities.
Applications, retrieval systems and agents. Extend the assessment to data pipelines, prompts, models, tools, deployment and ongoing operation.
A purchased model connected to internal data and tools can involve both. Assess what the system does and what your organization controls.
A person reviews the output before use. No sensitive information or connected action is involved.
Routine approval under delegated authority, with a clear route to report problems.
The three pillars establish the baseline, evidence and roadmap. This six-step lifecycle connects them to implementation and ongoing assurance.
Identify AI uses, owners, data and connections. Record visibility gaps.
Evaluate consequences and authority. Assign a justified use-case risk tier.
Define required safeguards, shared responsibilities and justified exclusions.
Apply agreed controls across identities, gateways, pipelines and operations.
Test effectiveness. Remediate, restrict, accept residual risk or stop.
Track activity, performance and changes. Reassess and verify remediation.
Know which agents, models and connectors are approved, what they do and who owns them.
How we verify it: Reconcile observed activity to approved records and resolve unowned assets.
Identify each agent and constrain its authority, including read versus write access and delegation on behalf of a user.
How we verify it: Attempt prohibited actions and verify that authorization and revocation work.
Apply sensitive-data restrictions, approved connections, DLP and checks at tool execution boundaries.
How we verify it: Test attempted data disclosure and unauthorized tool invocation.
Define quality and security acceptance criteria. Control changes to models, prompts, sources and tools.
How we verify it: Review release evidence and revalidate representative scenarios after material change.
Make required approvals enforceable. Name escalation owners and people authorized to intervene.
How we verify it: Test approval bypass, stale approvals and actions changed after approval.
Connect relevant inputs, versions, sources, tool calls, outputs and approvals so incidents and questioned decisions can be investigated.
How we verify it: Exercise alerts, suspension, rollback and recovery. Protect traces with appropriate redaction, access and retention.
Explore the five dimensions, scoring rules and the path to independent validation.
Read the white paperPDF · v0.2 · Consultation draft. This site’s v0.3 proposal adds explicit three-pillar delivery, use-case risk tiering and control implementation. Pilot validation remains ahead.
Evaluate specific assistants for instruction manipulation, data exposure, unauthorized actions and gaps in runtime evidence through agreed, scoped testing.
Explore Agent AssuranceBring milestones, evidence requests and working sessions into one shared view. Existing customers can sign in to their invited workspace.
Explore the Customer PortalBring your ambition and priorities. We’ll discuss where you are today and identify a useful starting point for your business.
Book ConsultationTell us how to reach you. No assessment commitment is required.
What to expect from the conversation