When Should a Company Use InferTrust™, and When Not?

InferTrust™ is built for organizations making consequential AI decisions in regulated or high-liability environments. If your AI recommendations affect patient

When InferTrust™ Is the Right Fit

InferTrust™ is designed for organizations where AI decisions carry real consequences and where the inability to prove what the AI did creates regulatory, legal, or financial risk. The clearest indicators that you need decision integrity infrastructure are:

• Regulated AI decisions: Your AI assists with decisions that fall under regulatory oversight (FDA, CMS, OCC, NHTSA, EU AI Act, state AI laws). Regulators are increasingly requiring verifiable evidence of AI behavior, not just documentation that you have policies.
• Litigation exposure: Your AI makes or assists with decisions that could be challenged in court. Medical malpractice, product liability, wrongful denial of insurance claims, fair lending violations, and structural engineering failures are all areas where the ability to produce tamper-evident evidence of AI behavior is a material legal advantage.
• Audit requirements: Your organization faces periodic audits (Joint Commission, SOX, ISO 9001, HIPAA) where you must demonstrate what your AI systems did during specific time periods. Conventional logs often cannot meet the evidentiary standard auditors are beginning to expect.
• Edge or offline AI: Your AI runs on devices without continuous network connectivity (medical devices, manufacturing controllers, autonomous vehicles, construction sites). Cloud-based audit systems cannot function offline. InferTrust™ signs records at the edge device before any transmission.
• High-stakes autonomous decisions: Your AI makes decisions autonomously above certain confidence thresholds, without human review. The higher the autonomy, the greater the need to prove exactly what the system decided and why.

When You Probably Do Not Need InferTrust™

Not every AI deployment needs cryptographic decision integrity. InferTrust™ adds value when the consequences of an AI decision are significant enough to warrant verifiable proof. You probably do not need InferTrust™ if:

• Internal analytics only: Your AI generates insights, dashboards, or recommendations that inform human decisions but do not directly trigger actions. If a human always makes the final call and the AI output is advisory, conventional logging may be sufficient.
• Low-stakes recommendations: Your AI recommends products, content, or internal prioritization where the cost of a wrong recommendation is low and there is no regulatory or legal exposure.
• Research and development: You are training and evaluating models in a development environment. InferTrust™ is a production infrastructure layer, not a training tool.
• No regulatory or legal exposure: Your AI decisions do not fall under regulatory oversight, and the likelihood of litigation or formal audit is minimal.

The Gray Area

Many organizations fall between these two categories. They deploy AI in areas that are not yet heavily regulated but are moving toward regulation (the EU AI Act is expanding coverage, state AI laws are proliferating, and sector-specific rules are tightening). For these organizations, the question is not whether they will need decision integrity, but whether they want to implement it before or after the first enforcement action in their industry. Implementing proactively is significantly less expensive and less disruptive than retrofitting during an active investigation.