Sequen AI

Sequen AI provides a behavior design and ranking platform for enterprise consumer applications, aiming to turn relevance into a revenue source. The company was founded in 2024 by CEO Zoë Weil, and technical co-founders Mo Afshar and Alexander Thom. The founding team includes leaders with experience from Google DeepMind, Anthropic, Meta, and Etsy. Weil, a graduate of NYU with a background in AI, previously served as Senior Vice President of AI at Citi and as a Staff Applied Scientist at Etsy, where she focused on personalized search and discovery.

Sequen AI came out of stealth in 2025 after a $6 million seed round led by Greycroft. In March 2026, the company announced a $16 million Series A round co-led by White Star Capital and Threshold Ventures, bringing its total funding to $22 million. The capital is intended to accelerate product development and hiring to meet growing enterprise demand. The New York-based company reports that it processes over 20 billion requests monthly and works with Fortune 500 companies.

The core of Sequen's platform is its proprietary Large Event Models (LEMs), which it invented. Analogous to how Large Language Models (LLMs) predict the next word, LEMs are specialized neural networks that predict the next user event. These models are trained on billions of user event sequences—such as clicks, scrolls, hovers, and views—to understand user intent and adapt experiences in real-time, even with sparse data. This technology is designed to shape user behavior, not just observe it, by using reinforcement learning to optimize for business outcomes like increased conversion, revenue, and engagement. The platform delivers its services through a low-latency API capable of sub-20 millisecond decisioning, which integrates infrastructure and AI to power in-session personalization, search, and recommendations. This allows enterprise clients to implement dynamic re-ranking and hyper-relevant user experiences without building and maintaining the complex infrastructure in-house.

Keywords: Large Event Model, LEM, behavior design engine, in-session personalization, reinforcement learning platform, dynamic re-ranking, AI-native infrastructure, user behavior optimization, real-time personalization, conversion rate optimization, adaptive consumer applications, Sequen IQ, Zoë Weil, Mo Afshar, Alexander Thom, enterprise AI, customer engagement, search and discovery, e-commerce personalization, revenue optimization