Aampe

Aampe is built for teams that want to move beyond A/B testing and segment-based campaigns. It assigns an AI agent to every user, running thousands of content variant tests in parallel to optimize engagement continuously. If you're at a company with large, diverse customer bases and have CDP/CPaaS infrastructure ready, Aampe can drive significant lifts—customers report 128% improvement in engagement and 135% increase in GMV. That said, this isn't for everyone. The system is largely a black box: you set goals and let agents learn, with causal signals and counterfactual simulations providing explainability. But if you need human approval per message or operate in highly regulated industries like finance or healthcare, this level of autonomy may be a hard sell. Compared to Braze or Dynamic Yield, which rely on manual segments and A/B tests, Aampe's always-on learning is more scalable, but those tools offer finer human control. The recent MoEngage acquisition could tighten integration, but also introduces uncertainty about long-term independence. Practical caveat: setup is quick (reported under 8 hours), but you need solid data hygiene—the platform's performance depends on clean behavioral signals. We'd reach for Aampe when the goal is maximizing engagement at scale and the team is ready to delegate optimization to AI agents.