About Aelo
We are building Aelo for marketers, founders and agencies who need to explain what an AI assistant actually said—not present another score nobody can audit.
Why it exists
A visibility percentage can point to a problem. It cannot explain the answer, prove a citation, or tell a team what to inspect next.
Aelo's operating belief
Aelo repeats buyer questions, keeps every successful and failed sample, attaches confidence to the estimate, and turns gaps into bounded investigations. The evidence remains available when the headline is challenged.
We would rather withhold a claim than decorate uncertain evidence.
Four product rules
01
A provider failure stays failed. Missing evidence does not become a zero, a synthetic answer, or a confident claim.
02
Every useful summary should lead back to the prompt, returned answer, sample, model and source evidence behind it.
03
Aelo can rank a gap and help a team organize work. Only a compatible follow-up measurement can show what happened next.
04
Marketing numbers need to survive finance, leadership and client review. Denominators and limits stay visible.
Built from India
Indian teams often evaluate global and local competitors in the same buying question, work in rupees, and need evidence their clients or leadership can inspect. That is a useful place to start building.
The method is not limited to one market. Aelo records model, region and measurement mode because context changes what an answer means. We expand by keeping those differences visible.
The goal is modest and difficult: report exactly what was observed, make the uncertainty legible, and help a team choose the next question worth answering.
Talk to the builders