AI Doesn't Know When It's Wrong. Emet Does.
Emet re-derives the figures an AI reports against your live source data, in code, so a wrong number is corrected before anyone acts on it. Now running in FUSE.
Emet re-pulls your source data and re-derives the figures an AI reported, in code, so a wrong number gets corrected before anyone acts on it. It works on the claims that can be checked against a source, and it says which ones could not be rather than counting them as passes. Emet is now running on FUSE analysis.
A wrong number from an AI looks exactly like a right one.
Same confidence, same formatting, no error message. It lands in a deck, a budget, a client email, and nobody finds out for a quarter.
We measured this on live client data using frontier models. More than one completed analysis in five contained at least one unsupported number, bad calculation, or claim the underlying data did not support.
Emet Does Not Read the Answer. It Redoes the Math.
Most tools in this category score AI output with more AI, which means a model grading work that another model just did, carrying the same blind spot that produced it.
Emet never asks the AI what the data said. It goes back to your source and works the number out again itself. Ask how last week's campaign performed, and when the AI reports 3.1x ROAS but the arithmetic gives 2.8x, you read 2.8x.
Presented at Google Search Central Live
On 30 September 2026, FUSE engineer Rafael Kovashikawa gave a lightning talk at Google Search Central Live Deep Dive Europe in Barcelona, "When AI Lies About Your Search Data". The aioseo.fr event summary reduced it to one rule:
Rafael Kovashikawa: an AI error-prevention rule, "no source, no number".
ROAST and PPC Land also covered the talk.
Two Things We Will Put on the Table
Not every sentence an AI writes is a claim about your data. Emet works on the ones that are: the figures, the derived math, the conclusions that stand or fall on what the source actually says. The rest it leaves alone and marks as unchecked, rather than quietly scoring them as passes and inflating its own record.
And our own dashboard was wrong about us first. It reported Emet failing roughly fourteen times more often than it actually was. Three reviewers caught it independently. We rebuilt the instrumentation so an unmeasured zero can never enter a rate, and every published figure now drills down to the responses behind it.
A verification company that has never published a correction is telling you something worse than a correction.
Emet Runs Inside FUSE
Ask a question of your connected sources and the answer arrives with its figures already re-derived. The check happens before you read the number, not after you have put it in a deck.
Emet holds its own read access to those sources, which is the part that matters, because it means it never has to ask the model what the data said. You can see a sample verification report on the Emet website, emet.so.
This is the same FUSE analysis that found the mobile audience our own product was turning away, and it works inside Claude through FUSE MCP, so it runs where your team already works.
It's time to trust your AI. Now there is a reason to.