IntentAxis
Enterprise AI search intelligence built around intent, evidence, diagnosis, recommendation, intervention and measured outcomes.
01 Trigger
Enterprise teams could suddenly see that AI answers were shaping demand, but nothing in the existing stack explained why an answer looked the way it did, or what to do next.
02 Idea
Start from intent instead of keywords. Gather evidence, diagnose the gap, recommend an intervention, then measure whether the intervention actually moved the answer.
03 Build
A convergence object more than a single tool: intent modeling, evidence capture across AI surfaces, diagnosis logic, a recommendation layer that produces real work items, and a measurement loop that closes back onto intent.
04 Learned
Measuring AI visibility and creating it are different disciplines. Dashboards describe. Interventions change things. The interesting product surface lives between them.
05 Status
Active. Building now, and the piece taking most of my attention.
06 Next
Tighten the loop from diagnosis to intervention so a recommendation can be executed and measured without leaving the system.
Keep moving
All 9 builds →
