Readiness Assessment accepts broad AI use cases. Deep Audit applies context-specific testing only where active testing is authorised and technically appropriate.
Governance Standard v2.0

Turn AI use case review into an assurance decision package

DeepAudit helps teams assess readiness, run authorised behavioural audits, trigger specialist reviews, and prepare SafeSpeed-ready handoff inputs for runtime control configuration.

Launch Readiness Assessment
SCAN ARCHITECTUREBLACK-BOX
1
Target Scope & API Endpoint
Provide URL & client access token
2
Controlled Behavioral Simulation
50–100 non-mutating scenarios
3
Evidence Assessment & Report
Structured audit outputs & PII logs

Why DeepAudit

DeepAudit is the pre-deployment AI assurance platform that helps organisations assess readiness, identify governance gaps, route specialist reviews, and generate evidence-based approval outputs before AI systems go live.

Informed by international AI governance guidance, including the Voluntary AI Safety Standard, the EU AI Act, the NIST AI Risk Management Framework, and ISO/IEC 42001.

Product Boundaries

DeepAudit focuses on pre-deployment assessment, evidence collection, and handoff compilation. It does not monitor active production systems, activate live runtime gateway rules, or enforce circuit breakers.

How it works

DeepAudit implements a progressive assurance pipeline from initial declaration to runtime handoff:

01Use Case Intake
02Readiness Assessment
03Diagnostic Routing
04DeepAudit Eligibility
05Contextual Behavioural Audit Plan
06Behavioural Evidence
07Specialist Review Triggers
08Assurance Decision Report
09SafeSpeed Handoff Package

What the report answers

DeepAudit delivers a structured AI Use Case Assurance Decision Report that answers the core questions required by AI safety committees, risk officers, and technical leads:

1. Which behavioural tests are relevant?

Contextually scopes adversarial cases based on RAG access, tool usage, and functional pattern mapping.

2. What failures or evidence gaps were found?

Exposes simulated bypasses, unsafe model outputs, or undocumented validation boundaries.

3. Which specialist teams need to review?

Triggers targeted review routing for Cyber Security, Privacy, AI Governance, Legal/Compliance, and Human Oversight.

4. Can the use case proceed, be deferred, or require remediation?

Applies automated gating rules to determine standard deployment status and owner-level risk sign-offs.

5. What evidence is required for closure?

Lists the exact retest scan runs or reviewer validations needed to resolve open assurance gaps.

6. What findings should be passed to SafeSpeed for runtime control configuration?

Compiles a draft handoff package of policy candidate templates, monitoring signals, and threshold recommendations.

Product Boundary Disclaimer
DeepAudit prepares SafeSpeed handoff inputs. Runtime enforcement is configured and operated in SafeSpeed.

INTERACTIVE FLOW ENGINE

End-to-End Governance Lifecycle

See how Deep Audit maps business context to automated readiness checklists, runs active safety scenarios, and compiles runtime protection controls.

Step 01 // Intake Context

Use Case Definition

AI Use CaseCustomer Refund
Lifecycle StagePre-production
Data ClassPersonal info
AI AutonomyTool execution
User GroupsCustomers
JurisdictionAU + US + EU
ASSESSMENT PROFILE
High Assurance Risk Tier
RECOMMENDED PATHWAY
Agentic AI Enhanced Audit
Start with context, not a generic scanner.

Establish AI System Readiness

Verify compliance checkpoints, define your scope of evaluation, and determine readiness stage before configuring behavioral simulations.