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Identify AI systems and risk-relevant work from the tools and exports your teams already use.
AI Governance Hub is built as one platform with one risk-intelligence engine. AI governance is where we start — every future solution reuses the same discovery, assessment, reporting, and monitoring foundation.
Every solution on the platform follows the same governance pattern:
Identify AI systems and risk-relevant work from the tools and exports your teams already use.
Classify and score each item with transparent, rule-based methodology — no black boxes.
Prioritized, framework-aligned recommendations your teams can act on.
Board-ready deliverables in HTML, PDF, Word, and PowerPoint.
Re-assess portfolios and track remediation over time — in Jira today, more tools to come.
Upload a Jira, Azure DevOps, Excel, or CSV export and receive an executive AI governance report — governance score, risk analysis, framework alignment, and a 30/60/90-day roadmap.
Start a free preview →Continuous AI governance inside Jira Cloud — discovery, risk registers, review workflows, and evidence capture. Runs on Atlassian Forge with no data egress.
Install from Atlassian Marketplace →Multi-format executive deliverables aligned to ISO/IEC 42001 and NIST AI RMF, with visual analytics dashboards on Growth plans and above.
See a sample report →Teams in these industries use our source-agnostic AI governance assessment today. Purpose-built modules — same engine, industry-specific risk models and regulatory context — are in development.
Governance for credit, fraud, AML, and trading AI — with regulatory context for RBI, SEBI, and global supervisors.
Register interest →Clinical AI inventories, patient-safety risk assessment, and HIPAA-aware governance reporting.
Register interest →Underwriting, claims, and fraud AI governance with model risk documentation.
Register interest →Factory AI, predictive maintenance, and quality-inspection AI under one governance register.
Register interest →Citizen-facing AI accountability, procurement risk, and public-policy alignment.
Register interest →Product AI governance, third-party model risk, and customer-facing AI transparency.
Register interest →Grid optimization, forecasting, and asset-monitoring AI with operational risk controls.
Register interest →Pricing, recommendation, and demand-forecasting AI governance with consumer-protection context.
Register interest →Clinical-trial AI, lab automation, and regulatory-submission readiness.
Register interest →Network AI, customer analytics, and service-assurance model governance.
Register interest →Everything we build fits one of these pillars — and reuses the same core engine, security model, and reporting layer.