Claim Audit
What does the product claim to reduce: time, headcount, error, cost, supervision, or complexity?
Agentic Systems Audit
Audit AI agents by real burden reduced.
Agentic Systems Audit evaluates whether AI agents, automation tools, and workflow systems reduce total work after supervision, verification, correction, context setup, failure handling, and risk are counted.
Hidden Work Audit
What new tasks appear: prompting, checking, escalation, correction, formatting, and compliance review?
Failure Surface Audit
Where can the agent act incorrectly, silently fail, hallucinate, or create downstream obligations?
Human Burden Audit
Does the system reduce cognitive load or simply transfer vigilance onto the user?
Delay Audit
Does the workflow reduce total elapsed time or only create faster intermediate outputs?
Decision Readiness
Can the output be used directly, or does it still require human reconstruction and judgment?
Audit output
Net delay scoreTime saved minus time added by setup, review, correction, and recovery.
Hidden work mapTasks that are displaced rather than eliminated.
Risk surfacePoints where failures become costly or invisible.
Adoption decisionUse, modify, restrict, reject, or retest.
For builders and buyers
Agentic Systems Audit is designed for founders, operators, analysts, investors, and teams that need proof before trusting automation claims.
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