See how policy drift monitoring works on your AI workflow.
Policy Drift Monitor
Detect when AI agents get pulled off objective by prompt injection, conflicting instructions, or long-context confusion. Monitor whether they still respect declared policy.
The problem
Surface-level outputs look fine. The agent is off-task.
Prompt injection, conflicting instructions, and long-context confusion pull agents off their intended objective. The outputs often look plausible, so the drift goes undetected until downstream consequences surface.
What Concordance does
Monitor the objective, not just the output.
Concordance tracks activation-level signals that indicate whether the agent is still pursuing the declared task and respecting the policy regime. When it is not, you get an alert with the evidence of what shifted and when.
How It Works
01
Declare policy boundaries
Define the task objective, policy constraints, and instruction hierarchy your agent should respect throughout its workflow.
02
Monitor latent state
Concordance tracks activation-level signals for shifts that indicate the agent is no longer pursuing the intended objective or respecting policy.
03
Flag injection and confusion
When prompt injection, conflicting instructions, or context corruption pull the agent off-task, get evidence-backed alerts for review.
Who Benefits
Enterprise Workflow Agents
Monitor multi-step agents for instruction drift across complex enterprise processes with branching logic.
Tool-Using Copilots
Detect when copilots misuse tools, exceed authorized scopes, or follow injected instructions over system policy.
Orchestration Systems
Track whether agents in multi-agent systems maintain task fidelity when receiving inputs from other models.
Security-Sensitive Deployments
Monitor for prompt injection attacks and context corruption where unauthorized behavior is a security risk.
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