AI red teaming and independent evaluation.

Third-party AI evaluation is testing of an AI model or agent by people outside the team that built it, so results are credible to buyers, risk teams and regulators. Awana provides it with calibrated human evaluators who grade your system blind against a golden set and report what they find unedited.

AI red teaming is adversarial testing: people deliberately try to make a model or agent misbehave, leak data, or take unsafe actions. Awana's red-teamers run jailbreaks, prompt injection, data-leakage and tool-misuse attacks mapped to the OWASP Top 10 for LLM applications, then retest after you fix them.

Not quite. Evaluation asks whether the system does its job well; safety testing asks whether it can be misused or cause harm. Awana covers both for products in production, and leaves dangerous-capability testing of frontier models, such as bio or cyber risk, to specialist evaluators.

Any team shipping an AI model or agent to customers, especially in regulated industries or where an enterprise buyer, auditor or regulator asks for evidence. Awana works with startups preparing for enterprise security reviews and with large companies that need evidence for their risk and audit teams.

Awana builds a golden set from your real usage, then calibrated human evaluators grade outputs blind against a rubric agreed with you. Awana measures inter-rater agreement, calibrates an LLM judge against the humans for daily runs, and reports results per metric with the graded set attached.

Awana starts from a threat model of your agent's users, data and tools, builds attack sets, and runs red-team sprints with human testers who know how agents fail. Every finding gets a severity, a reproduction and a suggested fix, and Awana retests once you've fixed it.

Awana tests for jailbreaks, direct and indirect prompt injection, sensitive data and system prompt leakage, unsafe agent actions, poisoned retrieval and memory, and misinformation. Findings are mapped to the OWASP Top 10 for LLM applications so your security team can track them.

Yes. Awana grades multi-step agent trajectories: whether the agent picked the right tool, passed the right arguments, respected its permissions, used memory correctly and finished the task. Red-team sprints also target the agent's tools and integrations.

Awana uses model-graded evaluation for speed, but anchors it to human grading. Calibrated evaluators grade a sample of the same cases, Awana measures how often the judge agrees with them, and adjusts the judge until it does, so daily automated scores stay trustworthy.

Awana's evaluation team works separately from any build team, with its own reporting line. Findings go to you unedited, methods and graded sets are shared with you, and Awana discloses up front if it helped build the system being evaluated.

Yes, as evidence. Awana's reports document methods, test results and retests in a form your team can map to the NIST AI RMF Measure function, ISO/IEC 42001 testing records, and EU AI Act accuracy and robustness testing for high-risk systems.

No. Awana provides independent test results and evidence; certification and conformity decisions stay with you and your accredited auditors. Being clear about that is part of what makes the evidence useful.

No. Dangerous-capability evaluation of frontier models needs specialist domain scientists and is led by dedicated safety evaluators. Awana focuses on product quality and misuse testing, and supplies trained evaluation capacity to specialist evaluators when they need it.

Awana signs a standard DPA and NDA before any data is shared, background-checks every evaluator and red-teamer, and works through your own SSO or OAuth with least-privilege access. Test sets and results stay in your environment, and PII is masked before human review.

Yes. Awana is United States-led, and its leadership holds an active US security clearance. For public-sector work, Awana scopes staffing to the agency's requirements, including US-based personnel where required.

Awana scopes it on the first call. A focused evaluation sprint or red-team engagement on one system usually takes a few weeks including the retest, and continuous evaluation runs before every release.

Awana works hourly or as a fixed-price project. Evaluation sprints and red-team engagements are fixed-price projects scoped to your system, and continuous evaluation is billed hourly. Awana gives you a quote after the first call.

Awana provides independent AI evaluation and red-teaming for teams shipping models and agents. Awana is United States-led, with calibrated engineers who grade AI for clients today, and works hourly or as a fixed-price project.