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 the notice actually has to say
Colorado AI Act consumer notice provisions have been in force five months. Most vendor templates do not meet them, and the deployer is on the hook.
Read →The August clock
EU AI Act general-purpose obligations enter enforcement August 2. Here is what changes for your board in three weeks.
Read →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 →How the gap shows up in production.
Illustrative scenarios, not client engagements. 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 vendor clinical-prediction tool informs triage decisions. The contract states performance benchmarks. No one has validated them against this hospital's own patient population, so no one can say where the model holds and where it quietly fails.
The board question.
A board asks, in writing, for the organization's AI risk exposure. A defensible answer requires an inventory of every model in production and a named owner for each. Neither exists in one place, so the response gets assembled from memory.
The compliance illusion.
An HR platform has an AI policy on paper and a review board on the org chart. Model updates ship on the engineering cadence. The governance record describes a system that stopped running months ago.
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.