Monty-UX is an AI-driven UX optimization platform. It takes a Monte-Carlo approach to your site or app — exploring the space of possible experiences, generating and validating interface experiments automatically, and testing the winners against real user behavior. All inside guardrails you define.
Powered by code-generative language models, Monty-UX turns your product into a living experiment queue — a new way of interfacing with your users, and their new way of interfacing with you. It is designed to:
Declare your standards — design guidelines, fixed elements, brand rules — and add one line of JavaScript. Your site is compressed into a typed grammar of its entities and actions.
Interactions are clustered into engagement groups from first-party behavior — differentiating users without cross-site cookies or bought data.
Candidate experiments are generated inside the grammar, mechanically checked against your guardrails, ranked per segment, and served — with a manual greenlight if you want one.
Results feed segmentation and ranking. A weekly report shows the winning experiments and who they served — with full session playback.
Every experiment is a widget; every widget is both a probe and a signal.
The model never writes arbitrary code against your site. It proposes experiments inside a typed grammar — your entities as nouns, your valid actions as verbs, your rules as constraints — and a deterministic checker verifies every proposal before it can be served. Fail the check, never seen. Generation happens offline in the grammar and expands to production code deterministically, so a new experiment costs functionally nothing.
The framework is specified in our published research — grammar, safety guarantees, serving mathematics, and the economics. Get the whitepapers →
We're in private preview with a small number of high-engagement sites while we test and refine our models. Want your users to meet their best version of your product?