The extraction engine
Not a generation engine. It captures what happened — decisions, wins, objections, changes — and that substance becomes the raw material. Same models plus different inputs is the only way to escape identical output.
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Ten agents producing marketing from what actually happened inside a business this week — built on the thesis that generic AI output is an input problem, not a model problem. Every competitor ingests style. Almost nobody ingests substance.
Not a generation engine. It captures what happened — decisions, wins, objections, changes — and that substance becomes the raw material. Same models plus different inputs is the only way to escape identical output.
Every claim an agent makes traces to a recorded event. This is how "never hallucinate" is enforced mechanically rather than promised in a prompt.
Each with a defined trigger, inputs, outputs, what it writes back, and what happens when it fails. Every one drafts; a human sends.
Designed and partially shipped \u2014 pricing and architecture are built, the full ten-agent runtime is not yet in production. There is nothing to measure yet, and a system that has not run cannot have an outcome. Listed at T1 for that reason.
We would rather show an empty measurement than a plausible one. A number nobody can check is worth less than an honest blank.
The pricing page leads with what the system will refuse to do. In a market whose central problem is AI publishing confident nonsense, three refusals do more work than nine promises — and the refusals are enforced by the ledger rather than by tone of voice.