Continuous Monitoring
Every change. A current assurance state.
Keep your AI assurance current.
AI systems change every day — models update, data shifts, policies evolve. Detect changes, understand their impact, and keep your assurance state up to date.
- Continuous assurance
- Auto re-evaluation
- Change alerts
- Audit-ready evidence
Detect change. Respond with confidence.
Assurance is a living process. Connect what changed to its impact, the right response, and the evidence behind your next decision.
Explore a source of change
Model changes. Clear next steps.
A new model version can change behavior even when the workflow stays the same. Connect the update to the assurance decisions it affects.
- Understand the change in context
- Prioritize the assurance decisions it affects
- Keep the response and evidence linked
- 01
Establish the baseline
Link the deployed model to its version, owner, and current assurance state.
- 02
Detect a version change
Identify the model update and the workflows that depend on it.
- 03
Re-evaluate the impact
Review affected evaluations and decide whether targeted testing is needed.
- 04
Update or escalate
Refresh the assurance state or route the change to an accountable reviewer.
Evidence stays connected
Model version · Impact assessment · Evaluation outcome · Review decision
See real-time state of your AI estate.
Bring every AI system, its trust score, risk level, and assurance state into a connected view — with the context to understand what changed and what needs attention.
A connected AI estate
See systems, ownership, and operational context together.
Trust and risk in context
Understand current assurance and where attention is needed.
A traceable response
Follow each meaningful change through review and evidence.
See how trust evolves.
A score is a starting point. Follow its trajectory, explore the assurance factors behind it, and put each monitored change in context.
View TrustScore DetailsTrustScore · Jun
Use the latest assurance state to guide the next review.
Behind the score
Five dimensions of assurance
Review the latest factor coverage alongside the overall trend.
- Policy & Controls92/100
- Behaviour & Safety88/100
- Data & Access84/100
- Human Oversight90/100
- Evidence Coverage96/100
Illustrative scores and factor values. Select a month to explore its score and review context.
Know what changed. See what comes next.
Move from an isolated alert to a clear next step. Connect model, tool, policy, and data changes to their impact, the right response, and the evidence behind it.
Explore the Monitoring LoopChange activity
Illustrative eventsModel change · Monitor
Model version updated
Before
Version 2.4.0
Detected change
Version 2.4.1
Understand the impact
A model update may change the behavior of workflows that depend on it.
Choose the right response
Compare affected evaluations and determine whether targeted reassessment is needed.
Evidence to retain
Version history · Evaluation results · Review decision
From change to updated assurance.
A connected cycle of observation, impact assessment, and evaluation keeps assurance aligned with your AI. Each response becomes the baseline for what comes next.
Observe model versions, data signals, tool access, and policy updates in the context of each AI system.
A detected change with its source and system context.
One agent. Many sources of change.
Keep model, data, policy, and business changes in view—so your assurance reflects the full context around each agent.
01
Model updates
New versions, retraining, and fine-tuning detected as they ship.
02
Data & access changes
Shifts in data sources, schemas, and access permissions.
03
Policy & governance
Regulation and internal policy changes propagated to agents.
04
Behaviour drift
Outputs drifting from certified behavior over time.
05
Compliance & security
Control failures and security posture changes flagged instantly.
06
Business context
Changes in purpose, scope, or ownership of the agent.
Clear state, clear actions.
Understand where each agent stands—and the response its current assurance state calls for.
Assured
Current evidence supports the approved use.
- What this state means
- No material changes since the last evaluation. The agent remains certified for its defined use.
- What happens next
- Continue operating within the approved scope, with monitoring in place for new changes.
- Connected evidence
- The current evaluation, approved scope, and latest monitoring signals remain connected.
Works with the entire CognitiveView platform.
Continuous Monitoring is the last link in the chain — feeding live evidence back into governance, control, and assurance.
AI Governance
Define the policies and standards every AI system must meet.
Agent Command Center
Register agents and control what they may do at runtime.
AI Assurance
Evaluate behavior and evidence against defined criteria.
Continuous Monitoring
Keep assurance current as models, data, and policies change.
You are here
Confidence through every change
Keep your AI assurance current.
Keep every agent’s assurance state aligned with reality—so your teams can move forward with the evidence and oversight they need.
- Detect change early
- Reduce risk
- Keep certification current
- Operate with confidence
