AI-TEVV
Live
Your AI passed the vendor's benchmark. That doesn't mean it works in your environment.
The federal government is adopting AI at massive scale: thousands of use cases across dozens of agencies, drawing on models from competing frontier vendors. Models behave differently depending on the platform, data, prompts, tools, guardrails, and mission workflows around them. AI-TEVV helps federal teams validate live AI systems through repeatable testing, measurable results, drift tracking, PII checks, and evidence-backed reports.
The same model is not the same system.
Connectivity, retrieval, guardrails, and the data it can see all shape how it behaves, so a benchmark measured in one context does not transfer to another.
Consider an air-gap deployed model with no path to the public internet. Cut off from live retrieval, it answers confidently from a knowledge base that may be years out of date, with no indication that it is doing so. The model that scored well on a vendor’s public benchmark is not the system your agency is actually operating, and many of these environments cannot be reached from the outside.
OTOT provides that assurance.
We independently assess AI systems. Our methodology is run-based and evidence-driven, and it runs inside your infrastructure so prompts, responses, and evidence stay within your authorization boundary and the capability stays within your team.
Assurance as a repeatable run, not a one-time review.
Every run preserves the prompts, responses, retrieved context, and metrics behind a finding: evidence you can defend to an auditor, not a dashboard that disappears.
We evaluate across seven domains, including hallucination and groundedness, bias and fairness, regression, safety, robustness, tone, and retrieval quality, and we map results to the frameworks agencies are operationalizing today, including the NIST AI Risk Management Framework.
The result is assurance brought to your environment, owned by your team, backed by evidence.