We turn AI search from a black box into a measurable, fixable channel.

Our mission

Buyer research is moving into AI conversations before the click, and most analytics stacks never see it. Brands are flying blind into a new channel that behaves nothing like classic search. Our mission is to give marketing teams the same engineering rigor for AI search that they already expect for performance channels: hypotheses, controlled experiments, attribution, and a feedback loop measured in days, not months.

We apply deep engineering to a marketing problem: item response theory, Markov models of brand persistence, and a custom agent fleet that tracks model updates as they ship, because we believe AI search deserves real science, not dashboards over scraped snapshots.

Built at IIT Delhi

AEOsim was founded at IIT Delhi by engineers and former researchers applying first principles to reverse-engineer AI search. We started from the retrieval and ranking systems that LLMs actually use, then built the BEACON engine (Bayesian Engine for Answer Convergence in Optimized N-space) to simulate them at scale.

Team

AEOsim is a small team of engineers and researchers. We believe that marketing is an engineering problem. The AEOsim team has developed the first multi-turn analytics platform for AEO, as well as proprietary simulation technology which is particularly effective for PDP optimization.