Own your AI evaluation.
Keep it private.
Only you know what good means for your business. So we build the private evaluation machinery your team owns and runs, and you measure what your AI is really worth, on your own terms, with criteria your vendors never see. We don't sell AI, and we don't evaluate it for you.
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You're spending millions on AI.
Know what you're getting back.
Enterprises poured tens of billions into AI and most of it can't be tied to a single dollar of P&L. The fix isn't another vendor dashboard. The company selling you the AI can't be trusted to grade it, and the moment you tell it what you value, it optimizes the number and pockets your playbook. You need evaluations you own, that your vendors never see.
The people building AI agree.
Public arguments from the people building AI: that private, owned evaluation is the one thing enterprises can't outsource to their vendors. Not endorsements of PrivateEval, just where the field is heading.
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“Private evals should capture whether a model is actually improving against outcomes that matter to the business (not just external benchmarks).”
Satya Nadella Chairman & CEO, Microsoft “A frontier without an ecosystem is not stable” -
“The evaluation that decides real money is private and per-firm.”
Sarah Guo Founder, Conviction · No Priors “The Untrainable” -
“You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful.”
Satya Nadella Chairman & CEO, Microsoft “The Reverse Information Paradox”
And the risk of ignoring it: when Figma partnered with Anthropic, Anthropic shipped a competing product months later, and investors flagged the conflict. Show your AI vendor your playbook, and your AI vendor can become your competitor.
CNBC Yahoo FinanceBuild. Operate. Transfer.
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Build
We get your data AI-ready and set up the eval infrastructure on it, inside your perimeter: data structures, a harness, and the scoring scaffolding. You define what counts as good, because it's your business, not ours.
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Operate
If you want, we run the loop as a bridge, maintaining ground truth and re-scoring on every model swap, until your team is ready to take it fully in-house. Operating is a phase, never the product.
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Transfer
You own the loop, the data, and the open methodology outright. It runs inside your walls, and the vendors you're evaluating never see it.
A company's AI vendor reported its support-AI was deflecting most of its tickets. The eval loop the company owned showed it delivered only 40% of what was claimed, surfacing $1.2M of renewals they'd have bet on the vendor's number.
Why the obvious options don't work.
- Your vendor's dashboard The company selling you the AI can't be the one grading it. Tell them what you value and they optimize for exactly that: the ROI looks real while they mark their own homework, and your playbook is now theirs.
- Building it in-house You could stand up an eval team over a year or two. We bring the machinery and the know-how now, and hand you the keys, so you own it outright without the multi-year detour.
- The big consultancies They build and resell the AI they'd be assessing. We sell no AI and take no cut of the answer, so there's nothing for us to protect when the number comes back.
- Off-the-shelf eval tools Dev-facing widgets that score models in CI. We build an owned, private capability pointed at your business's own ROI question, kept invisible to the vendors you evaluate.
We have no stake in the answer.
You own the loop and the methodology, so the number is yours, not ours to spin. And because we sell no AI and take no cut of the result, we've nothing to protect when it comes back. These commitments are contractual, written into every engagement.
- No model resale We never sell AI and take no rev-share. No stake in which model you pick.
- No success fees A flat subscription, never priced on the result, so the number stays honest.
- No data egress Everything runs inside your perimeter. Your evals stay invisible to the vendors you evaluate, and no one's model trains on your data.
Built by people who've actually done it.
PrivateEval is built by a team that pairs a former Safety & Privacy tech lead from a frontier AI lab with deep large-scale data engineering. That is the exact pairing this work needs: people who make sensitive data evaluable, and who keep it inside your walls while you do. Names on the first call.
Land with a sprint.
Expand into the loop you own.
- 01
Proof Sprint
A running, customer-owned eval harness on your data, a quantified before/after baseline, and a memo you can take to your board.
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Private Eval Loop
Your loop, running continuously. We operate it as a bridge, maintaining golden datasets and re-scoring on every model swap, until your team takes it in-house.
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Platform
Owned-loop seats for your team, and the tooling to run private evals across every AI initiative you have. The capability, fully in your hands.
Get started
Know what your AI
is actually worth to you.
We take on a handful of teams at a time. No pitch, just a working session to see if there's a fit.