What your AI actually does. Not what it's claimed to do.
Most organizations can describe what their AI is supposed to do. Far fewer can show what it actually does, under load, in production, on the cases that matter. Veracity AI closes that gap.
Every AI system falls into one of four states.
We classify systems on a single axis: how well the organization can defend what the AI is doing. The classification drives the engagement.
Documented behavior, evidence of testing, monitored outputs, clear escalation paths. The bar most organizations think they hit. Most do not.
Performance is real but uneven. The system handles known scenarios well, fails silently on edge cases, and no one is sure where the line is.
It produces outputs, but they do not change decisions. Often a model layered onto a process that already worked without it.
Behavior diverges from policy, claims, or contracts. Sometimes by design, sometimes by drift. This is where governance has to engage first.
Where does your AI governance actually stand?
Answer three questions for an instant classification. The full diagnostic returns a written read of which tier your systems fall into, in about ten minutes.
The compliance gap is widening faster than the tooling.
The EU AI Act is moving from text to enforcement, with major deadlines landing between 2026 and 2027. State-level AI disclosure rules are arriving in the US, and procurement teams at large buyers are requiring documentation most vendors can't produce.
None of this needs to be alarming, but it does need to be answered. The work we do is closer to financial audit than software development: structured questions, evidence, written conclusions, and a paper trail you can hand to a regulator, an acquirer, or your board.
Writing on the work.
What an AI governance assessment costs, and what you get
Plain pricing for independent AI governance work: a free diagnostic, an $8,000 to $12,000 readiness assessment, and a $3,000 to $5,000 monthly advisory retainer. What drives the number, and how it compares to a platform or a Big Four engagement.
Read →Audit or platform: which AI governance investment do you actually need?
AI governance platforms and independent audits solve different problems. A plain guide to which one your situation calls for, and why the distinction matters before you spend.
Read →The EU AI Act timeline after the Digital Omnibus: what actually changed
The Digital Omnibus pushes the EU AI Act's high-risk deadlines back by more than a year. A clear, sourced read of the new dates, what did not move, and what it means for governance planning.
Read →What we keep finding in production.
Representative patterns, anonymized. Different sectors, the same shape: a gap between what the AI is claimed to do and what it can be shown to do.
The vendor black box.
A regional health system ran a vendor clinical-prediction tool that informed triage, but could not show it performed as the contract claimed on its own patient population. The audit defined exactly where it held and where it quietly failed.
The board question.
A bank board asked, in writing, for the organization's AI risk exposure. No one could produce a defensible answer. We built the system inventory and scored it on TRACE.
The compliance illusion.
An HR platform had an AI policy on paper, but model updates shipped without review. The governance record described a system that was no longer running.
Three ways to start.
A 10-question read of your governance maturity, with a written assessment and prioritized next steps.
Learn more →A structured assessment of what your governance infrastructure can sustain under regulatory scrutiny. Fixed fee, 2 to 3 weeks.
Learn more →Ongoing governance review of model launches, vendor decisions, and policy changes, on retainer.
Learn more →Independent. Methodical. On the record.
Veracity AI is an independent practice, led by founder and principal Gary Trautmann. We do not build AI systems, sell models, or carry a stake in any vendor or framework. The independence is the product.
Read the full background →- Ph.D. Organizational Development and Leadership, University of Arizona. Dissertation on AI bias mitigation and governance.
- TRACE Registered methodology. U.S. Copyright Office, TX 9-584-804.
- ~3 decades Financial services technology, including problem management at enterprise scale.
- Since 1986 Formal training in AI and expert systems.
Find out which tier your AI actually falls into.
Ten questions. About ten minutes. A written read of where your systems stand and the two or three things to address first.