Know what AI is being used—and why.
Start with a shared view of registered AI assets and the risks and responsibilities attached to them. Three modules help teams establish this foundation.
AI Registry
Record each registered AI asset’s owner, purpose, risk level, and status so responsibility is clear.
AI Risk
Maintain a register of AI risks and assess their potential impact to help prioritize follow-up.
AI Compliance
Organize governance controls and track them against the compliance frameworks configured for your organization.
Turn oversight into a working process.
Give teams a defined way to apply policies, review changes, and assess output quality.
AI Policies
Apply configured policies that can block activity, provide guidance, or record events for review.
AI Reviews
Route high-risk AI changes to authorized people for review, with clear responsibility for the decision.
AI Evaluation
Assess AI output quality and compare evaluations to identify where performance may be deteriorating.
See the evidence behind the activity.
Bring operational records and governance information together so teams and leaders can understand what happened and where to act.
AI Audit and Lineage
Trace the relationship between inputs, AI outputs, and subsequent actions. Review the records connected to an AI-assisted decision.
AI Analytics
Review usage, policy violations, and patterns across registered AI assets to guide investigation and follow-up.
Command Center
Give leaders a consolidated view of governance status and issues requiring attention.
Governance alongside everyday operations.
A factory incident, a hospital coordination task, and a motor claim involve different work. They share a need for clear permissions, review points, and records of AI assistance and human decisions.
For an illustrative equipment incident, AI helps classify the issue and surface relevant procedures. The workflow routes the task to the responsible team. When an escalation needs approval, an authorized manager reviews the context and decides. The decision is recorded against the work item.
The Enterprise AI Harness connects the context, tools, workflow, and human handoffs that progress the task. BlissOS Control supplies governance oversight: which configured policies apply, what requires review, and which records support follow-up.
Start with a clear governance scope.
BlissOS Control is a cross-industry governance offering that can accompany BlissOS operational solutions. Its scope covers AI assets and workflows managed within BlissOS and the integrations included in your deployment.
Start with a set of AI assets or a workflow that matters to your team. Agree the owners, policy settings, review responsibilities, evaluation criteria, and records you need. BlissJunction will confirm the modules, configuration, and integrations for that scope.
- Which AI assets and workflows should be included?
- Which changes or actions need an authorized reviewer?
- What evidence will teams and leaders use to assess progress?
Common questions
Does BlissOS Control discover and govern every AI system automatically?
Coverage is defined around registered AI assets, workflows managed within BlissOS, and integrations included in the deployment. Agree which systems and actions are in scope with BlissJunction.
Does AI Compliance guarantee certification or regulatory compliance?
AI Compliance helps organize governance controls and track them against configured frameworks. Your organization remains responsible for interpreting applicable requirements and assessing whether its controls meet them.
How is AI governance different from ordinary access control?
Access control defines who can use a capability. AI governance also covers the AI asset’s purpose and owner, policies, risks, evaluations, reviews, decision records, and oversight.
Can we discuss governance without choosing an industry suite first?
Yes. Start with your AI governance needs. BlissJunction can help define an appropriate scope and explain how Control can accompany operational solutions.