aiFObserve
aiFObserve
An AI agent may hold valid credentials while taking actions that exceed its business authority. aiFObserve helps teams review AI usage, costs, security signals, and the evidence behind those observations. With identity and application event integration, that foundation can support a more consequential question: What did AI agents actually do after authorized access?
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Buyer |
Question to answer |
Value to the decision |
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CISO |
Which identities and AI services show risky behavior, and which business actions followed. |
Prioritize investigation using source evidence, confidence, and business context. |
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CFO and controller |
Did an agent alter a supplier, post a journal, grant a credit, or release a payment outside control policy. |
Focus review on financial processes and assess cost against accepted outcomes. |
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Internal audit and external auditor |
Can the action timeline, approval, source population, and rule be reproduced. |
Use organized evidence to evaluate exceptions and request targeted follow up. |
Identify potential conflicts such as an agent changing a supplier bank account and a linked agent releasing payment, or preparing and posting the same journal. This use case requires ERP transaction logs, verified delegation, independent approval data, and an added evaluator for ordered events.
Combine AI traces and tool activity with identity and business application events to show actions and outcomes. Distinguish a request, an allowed request, and a committed business change. Network and session signals help prioritize review when detailed application records are unavailable.
Review provider and application usage, cost concentration, trends, forecast assumptions, suspicious volume, and unapproved destinations. Link business completion and finance data to measure cost per accepted result and validate ROI.
Deployment fit: organizations using AI across finance, procurement, HR, customer operations, and other controlled processes, particularly where evidence is spread across multiple applications and security platforms.
What aiFObserve provide:
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Available v2 analytics |
Buyer benefit |
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Usage cost and trend analysis |
Locate concentrated spend and changing usage by available user, provider, application, tenant and time evidence. |
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Security findings and custom rules |
Review supported access, traffic, volume and policy signals with triggering session details and threshold evidence. |
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Compliance evidence exports |
Use CSV summaries, field coverage, source confidence, provider location and boundary findings in review workpapers. |
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Recommendations and projections |
Assess proposed actions and planning scenarios with their assumptions and data quality limits. |
For a transaction assurance deployment, add the agent and human owner, delegation chain, application actions, affected objects, approvals, policy version, source references, and reviewer disposition. ERP and application adapters and these additional evidence fields are part of the integration scope. Governed retention, integrity checks, case workflow, and enforcement connections must be designed with the organization.
Illustrative planning model, not a measured customer result: 120 review packages per year at 4 hours each require 480 hours. Reducing preparation to 1.5 hours saves 300 hours. At a fully loaded rate of $125 per hour, that represents $37,500 of annual staff capacity. Measure whether that capacity becomes an actual cash saving or is redeployed to additional review.
A separate modeled case uses $1.2 million in annual AI spend. If invoice reconciliation confirms 5 percent avoidable spend and remediation actually removes it, the annual saving is $60,000. Combined gross benefit is $97,500 before subscription, integration, review effort, and operating costs. Avoid double counting labor and spend savings, and do not assume audit fee reductions or avoided fraud losses.
Select one process, one entity, and a defined review period. Agree the source population and control rule. Test known conflicts and legitimate exceptions. Measure completeness, attributable actions, approval coverage, investigator accuracy, preparation time, and reconciled spend. Security, finance, and audit should review the same evidence package before expansion.
aiFObserve Compliance Evidence Capabilities: aiFObserve analytics include general evidence reporting and 11 framework reports, including SoX evidence report and full cross application SoD control engine extensions.
While aiFObserve provides management and audit review, control effectiveness and audit conclusions remain with the responsible reviewers.