How do you know the AI you deployed actually works?
Sovrano AI measures your AI on the regulated work you use it for, graded by domain experts, with evidence you can put in front of a risk committee.
Evals are the new KPI.
Every AI system you deploy now needs a number that says how well it does the job. General benchmarks show what a model can do. You need to know what your system does on the regulated work in your market, measured before you scale and ready when someone with authority asks.
Someone asks, or you're about to scale
A supervisory inquiry, an internal audit, a high-risk sign-off, or a fleet of agents about to roll out. The question is always the same: how do you know this works, and can you defend that answer?
Generic scores miss the job
A model can top a public leaderboard and still miss Spanish consumer-credit rules or a French insurance disclosure. What counts is capability in your regulated workflow.
A record of your own
You carry the deployment risk, so you need independent evidence of performance to point to when it matters.
Independent, expert-graded evaluation of the AI you run.
Every engagement runs in four steps: Specify, Measure, Improve, Re-measure. Your experts arbitrate, our practitioners do the volume. You get a verdict, a failure analysis showing where the system breaks, and a record you can hand to a risk committee, an auditor or a supervisor.
Specify and measure
We agree the tasks and the rubric with your experts, who settle what good looks like. You give us access under NDA, and our practitioners grade the system on a held-out set of regulated tasks that stays on our side, so it stays a fair test. You get the score, the failure analysis and the evidence.
Improve and re-measure
Where the evaluation finds weak spots, we can author expert training data to fix them: worked examples, preference comparisons and reasoning traces. Then we measure again. This step is optional, and it is walled from the evaluation set, so the measurement stays honest.
Independent by design.
A deployer needs a measurement with no stake in the result. Sovrano AI does one job in your stack: it measures, and reports what it finds. We keep it that way on purpose.
Independent of the model
The party measuring stands apart from the system being measured. That separation is what makes the verdict independent.
The wall rule
Evaluation data and any training data we produce for you are kept separate. We never train on, or sell data derived from, the held-out evaluation set.
Held-out by design
The scored tasks stay on our side and are refreshed over time, so every review measures the system fresh.
The same method underpins EuroExec, our public benchmark of frontier-model performance on European executive work. The public leaderboard shows how the method reads across the major models; your engagement is the private, contamination-safe version run on your own systems.
Evidence for the AI Act's high-risk obligations.
As the AI Act's high-risk obligations phase in, AI used in Annex III cases such as credit scoring, insurance pricing and employment comes under rules on risk management, data governance, accuracy and human oversight, applying from 2 December 2027. Most providers self-assess their own conformity, without an external body. We help you clear that bar defensibly, and show where your system falls short before a supervisor or your board asks.
Where we fit in your compliance case.
You own the compliance case, and conformity certification sits with notified bodies. We produce the independent, expert-graded evidence and the provenance record that make your case defensible. Where our evaluation maps to specific obligations:
Risk management
Recurring re-evaluation and drift detection feed a continuous risk-management record for the model in production.
Data governance
Provenance and consent documentation for any expert data we produce, generated from the evaluation metadata itself.
Human oversight
Expert human review and structured failure analysis you can cite as evidence of meaningful oversight.
Accuracy & robustness
Domain-specific accuracy measured on real regulated tasks, with per-item grades and agreement statistics.
FRIA support
Technical input for the fundamental-rights impact assessment that deployers of high-risk systems must complete.
Provenance
Consent-chain and data-protection documentation on the expert data, with EU-resident evaluators throughout.
Regulated European enterprises deploying AI in the work that matters.
The organizations
Banks, insurers and healthcare groups first, then any regulated European enterprise putting AI into supervised decisions, including large employers automating hiring. Teams already used to independent model validation under Basel and Solvency.
The people
Heads of model risk, compliance and data-protection officers, and the AI leads scaling agents across the business.
Where it fits
Alongside your model-risk and validation function. Your experts arbitrate, our practitioners do the volume, and your team commissions and cites the result like any independent validation.
When it starts
When a system goes live in a high-risk use case, when a supervisor or auditor asks, or when a fleet of agents needs a baseline before it scales.
Is this you? One test decides it.
The test: is AI making or shaping a decision someone could challenge?
AI in a decision that counts
Models or agents that decide or shape credit, hiring, pricing, eligibility, claims, fraud checks, customer advice or clinical triage. If someone could contest the outcome, you need to defend it.
Pure productivity use
AI that drafts, summarizes, translates or writes code, while a person makes every decision that counts.
The assistant that became the decision
A support agent that now commits the company. A screening tool that filters candidates before a human looks. If you're scaling agents, you're probably here.
A verdict you can defend.
Every engagement returns an evaluation report written for a risk and compliance reader: the score, where the system fails and why, and the documented evidence trail. A sample of the shape:
The deployed credit-advisory agent was evaluated on 420 held-out tasks drawn from Spanish and German consumer-lending workflows, each independently graded by two domain specialists against a shared rubric (Krippendorff's alpha 0.81). Overall expert-graded accuracy was 73 percent. Performance held on affordability assessment but dropped sharply on regulated disclosure wording and on cases involving vulnerable-customer handling, where 6 of the 10 lowest-scoring items clustered. Full per-item grades, rater IDs, and the failure taxonomy accompany this summary.
{
"item_id": "credit_de_0188",
"domain": "consumer_lending",
"jurisdiction": "DE",
"task": "affordability_and_disclosure",
"rater_ids": ["ev_08", "ev_23"],
"expert_score": 2,
"max_score": 5,
"agreement": true,
"failure_tag": "regulated_disclosure_omission",
"rationale": "Agent computed affordability correctly but omitted the mandatory pre-contractual APR disclosure.",
"rubric_version": "v2"
} Illustrative only. Your systems, domains, jurisdictions, and rubric are whatever the engagement needs. Numbers shown are not from a real client.
Three ways to work with us, each scoped to your system.
Most enterprises start with one scoped evaluation, then move to standing oversight. Every engagement is fixed-price, quoted after a short discovery call.
Independent Evaluation
A scoped, expert-graded assessment of one deployed model or agent on real regulated tasks in your domain and market. Score, failure analysis and documented evidence.
Oversight Retainer
Recurring re-evaluation, drift detection, and human-oversight documentation for a system in production, feeding a continuous Article 9 risk record.
Provenance & Documentation
AI Act Article 10 and GDPR provenance and consent packages, generated from the evaluation metadata. Standalone or added to an evaluation.
FRIA technical support and improvement data are scoped separately. We price for expert-tier work, and the scope and fixed quote come out of the discovery call.
What model-risk and compliance teams ask first.
For a deployer such as a bank or insurer, no. The obligations apply when your use case falls under Annex III high-risk, most often credit scoring, insurance pricing and employment decisions. The Act then asks you to show the system is fit for use, monitored and overseen, and for most of these cases you self-assess. Independent, expert-graded evidence is the strongest way to meet and defend that. It is a choice, and we say so plainly.
No. We evaluate through a controlled endpoint under NDA. We do not need your weights, and we do not need real customer records to run a scoped evaluation. Your systems and data stay on your side throughout.
Vendor benchmarks show what a model can do in general. We measure what your deployed system does on your regulated tasks, in your market, graded by experts, from a party with no stake in the score. Your risk function needs both.
Yes, because we wall the two apart. The tasks we score you on are held out and never used for training, and any improvement data we author for you is kept separate from that evaluation set. The verdict is only worth something while that wall holds.
EU-resident specialists in finance, law, insurance and medicine, trained on your rubric before production work, with quality review built in. They do the volume; your own experts arbitrate the rubric and the hard calls. The same method runs the EuroExec public benchmark.
A scoped Independent Evaluation of a single system is the usual entry point. It is fixed-price, time-boxed, and gives you a real verdict you can take to your risk function before deciding on anything standing.
Start with one system and one question.
The fastest way in is a short discovery call: tell us which deployed system you need a defensible read on, and we'll scope a fixed-price evaluation.
A scoped evaluation
One model or agent, one regulated workflow, expert-graded on real tasks. A verdict and failure analysis you can take to your risk committee.
A standing oversight relationship
Once the first evaluation proves out, move to recurring oversight and a continuous compliance record for the systems that stay in production.
A short call to scope one evaluation
We reply within one business day.
Request a call.
We use your details only to reply about your request. We reply within one business day.
Request a callThe independent read on whether your AI is good enough to trust.
Expert-graded evaluation of the models and agents you deploy in European regulated work, with the evidence trail to defend them. Independent by design, GDPR-native.
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