Before you act on the number your AI gave you, get a second opinion that recomputes it.
AYA Second-Opinion takes the data answer your copilot just produced, independently re-derives it against the same database, and checks that it actually answered the question you asked. You get a verdict backed by a recompute, not a confidence score dressed up as a control.
Second-opinion a batch of your answers See a sample recompute verdict
THE PROBLEM
Your analytics AI reads a question, writes some SQL, and hands back a number that reads as authoritative. Most of the time it is fine. But sometimes it answers a slightly different question than the one you asked, joins on the wrong grain, filters a date the wrong way, or quietly returns a plausible figure that is simply wrong, and because the sentence around it is fluent, nobody catches it until it is in a board deck, a filing, or a chart in front of a regulator. The usual safety net, asking the same class of model to grade its own answer, is just fluency checking fluency (a confidence number pretending to be a control), which is exactly the thing that does not survive scrutiny. In Q1 2026, AI hallucinations acted on as fact drew more than 145,000 dollars in sanctions and put fabricated work in front of courts, and as of August 2, 2026 the EU AI Act turns "prove what your AI did" into a board-level obligation for high-stakes systems, so this stops being a quality nicety and becomes a control with a date on it.
HOW IT WORKS
Second-Opinion does not author your query, and it does not sit in your pipeline, it sits to the side and re-derives the answer independently. For a given question against your attached database, it reconstructs the SQL from a bounded plan (the model is demoted to that plan, it never writes the query directly), self-verifies that SQL with two native checks, a recompute oracle and an intent-align oracle, and then executes it under validation. Where both native gates pass, you get a verified answer and an intent verdict that says yes, this really answers the question you asked. Where they do not, it fails closed and flags the result as unverified rather than handing you a green check it cannot stand behind. The verification plane is deterministic and model-free end to end, and it never ingests your copilot, your prompts, or your weights.
WHAT YOU GET (the second-opinion verdict)
For each high-stakes answer you send: - the independently recomputed answer, re-derived from your source data, - an intent verdict, verified or flagged unverified, that says whether the recompute answered the question actually asked (not a near-miss rephrasing), - the both-native-pass gate, the honest signal that recompute and intent-align both held, - the constructed SQL, so the re-derivation is auditable line by line, - the agreement or disagreement against the answer your AI produced, with the disagreement kind and the re-derived answer as the receipt, plus the cost and runtime delta.
A verdict you can act on, not a score you have to defend.
WHO IT'S FOR
Data, analytics, and RevOps teams shipping AI-generated SQL and text-to-SQL copilots into decisions where a wrong number has consequences, first, then legal, healthcare, and fintech teams where an AI-computed figure lands in a filing, a chart, or a court exhibit. If a wrong number from your analytics AI can cost you a decision, a filing, or an audit, this is for you. If a wrong number costs nothing, it is not.
PRICING (the ladder)
We price the ladder, not a single number, and every number below is a hypothesis we validate with you, not a commitment. - Pilot, a fixed-price paid proof on your own batch of high-stakes questions and your AI's answers. You see the second-opinion verdicts and the disagreement report before you commit. - Value-metered, per recomputed answer, once the pilot proves the delta. Your copilot keeps running, we second-opinion the answers that matter. - Platform, license the deterministic recompute verifier into your data stack.
IP is licensed, never assigned. The verifier stays ours, the proof is yours. Any step that takes your money is gated and confirmed before it runs, nothing charges silently.
THE PROOF (dogfood)
We run this discipline on ourselves before we sell it. The construct-and-self-verify recompute underneath Second-Opinion is the same moat AYA uses to answer its own data questions internally, and it is answer-source-agnostic, so it grades AYA's own generated answers exactly the way it grades a buyer's copilot output, we eat the verifier we sell. And the product's own build left a receipt, the deliverable pattern was scored by the pattern quality runner and both of the atoms it composes were verified on disk before this page was written. That is the same kind of evidence trail this product produces for you.
HONEST NOTE
We would rather under-promise. Second-Opinion has been built and structurally verified, the pattern composes, the atoms resolve, and the recompute and intent-align oracles underneath it are the already-wired code moat, not something we stood up for this launch. What it has NOT done yet is run against a live buyer database or a real batch of your AI's answers, that is the first live test once read-only credentials and a sample batch are in hand, and we will say so plainly rather than imply a proof we have not run. One more honest line, the shipped version re-derives its own SQL from your question and returns that as the second opinion, if you want it to instead judge a specific SQL string your own AI wrote, that is a small, named addition we have not built into this bundle. Where both native checks pass we give you a verified answer, where they do not we tell you and flag it, we never manufacture a green check. That refusal to fake certainty is the whole point.
Second-opinion a batch of your answers
*This page is a specification. The capability it describes is not built yet, and nothing here is a claim that it runs today.*