The foundation model for transactional behavior.
We are building a new class of foundation models for sequential human behavior in retail, payments, and finance. Large Behavioral Models (LBMs) that (1) learn directly from transactional behavior, (2) generalize across users, merchants, and geographies, (3) transfer to downstream applications including personalization, credit scoring, and fraud detection. Ultimately, we're pursuing general behavioral intelligence: what we think of as the AGI of human behavior in the digital economy.
Research
2026-06-03
Scaling Laws for Behavioral Foundation Models over User Event Sequences
We establish compute-optimal training recipes for behavioral foundation models across roughly 600 experiments spanning four orders of magnitude of compute. Behavioral models start data-hungry at small scale before converging toward the Chinchilla heuristic, and the metric you optimize shapes the scaling law itself.
2026-02-05
Large Behavioral Models: A Foundation Model Paradigm for Human Actions
We introduce Large Behavioral Models (LBMs), foundation models trained on chronological sequences of human actions. BehaviorGPT, a frontier LBM, delivers double-digit sales uplift for retailers and payment companies.
2025-07-15
BehaviorGPT: aesthetic purchasing preferences from behavior
We learn aesthetic preferences from purchasing and engagement sequences (how people discover, save, and acquire art and design) rather than from static labels alone. Trained on 215 billion human interactions across major art and design platforms.