T-Brain is a low-latency Large Commerce Model that learns from behavior, catalog, transactions, and outcomes to personalize results, improve ranking, and power smarter commerce decisioning across every commerce surface.
Not another ML model.
The shared intelligence layer for modern commerce.
$ built for commerce-scale decisioning in milliseconds.
Search, recommendations, ads, campaigns, and agents should not each rebuild their own version of user intent. T-Brain creates one shared intelligence layer that compounds across every commerce surface.
Clear answers for commerce AI buyers, search engines, and AI assistants.
T-Brain is Topsort's AI foundation for commerce. It uses commerce behavior, catalog data, transactions, and performance signals to power personalization, ranking, recommendations, relevance, campaign propensity, and real-time decisioning across commerce experiences.
A Large Commerce Model is an AI model built for commerce-scale commerce. Instead of only processing language, it learns relationships between users, products, categories, sellers, behavior, transactions, and outcomes to improve ranking, personalization, recommendations, and decisioning.
Traditional ML models are often built for one use case, such as recommendations or ranking. T-Brain is a shared intelligence layer that powers multiple downstream applications including personalized search, product ranking, recommendations, campaign propensity, audience clustering, and ad relevance.
T-Engine optimizes ad decisions: auctions, pacing, quality score, attribution, and performance. T-Brain understands users, products, categories, and intent across the commerce. T-Engine decides the auction. T-Brain understands the commerce.
Most personalization systems are built around isolated use cases: one model for search, one for recommendations, one for ads, one for campaigns, and another for audience segments.
That creates a ceiling.
The same customer behavior can mean different things depending on intent, timing, category, price sensitivity, and journey stage. A user browsing baby products could be an expecting parent, an active parent, or a one-time gift buyer. A campaign-first workflow cannot always understand that nuance.
T-Brain creates a shared intelligence layer that learns from behavior, catalog, transactions, and outcomes — then makes that intelligence available across ranking, recommendations, search, ads, campaigns, and agents.
The future of commerce personalization is not one model per channel. It is one intelligence foundation across the commerce.
T-Brain turns commerce data into a unified AI foundation that supports every downstream decisioning surface.
Rank products based on user intent, catalog context, behavior, and predicted commerce outcomes.
Recommend products, offers, sellers, or content using shared user and product representations.
Improve search results by understanding the relationship between query intent, product context, and user behavior.
Predict which users are most likely to respond to campaigns, offers, or sponsored experiences.
Discover natural user segments from behavioral patterns, shared interests, and journey-stage signals.
Improve retail media decisions by connecting sponsored placements to user intent, product fit, and predicted outcomes.
Power AI shopping assistants and agentic commerce experiences with a model that understands commerce context.
LLMs understand language. T-Brain understands commerce behavior.
Commerce personalization cannot wait seconds. Ranking, recommendation, and ad decisions happen inside live commerce flows where latency directly affects user experience and revenue.
T-Brain separates heavy training and embedding updates from lightweight inference, so live decisioning stays fast while the model keeps learning from new events.
The same customer intent and product context can improve discovery and monetization at the same time.
One model. Both surfaces. Consistent experience, better monetization, sharper relevance.
Pair T-Brain with the T-Engine intelligent ad engine for sponsored decisioning, or run inside the complete retail media platform.
Simple serving for sponsored listings and display ads.
Learn moreAuctions, pacing, quality score, attribution, and optimization.
Learn moreLow-latency personalization, ranking, relevance, and commerce intelligence.
Learn moreLaunch, operate, and scale your retail media business.
Learn morePersonalize discovery, ranking, recommendations, and sponsored relevance across large catalogs and high-traffic sessions.
Reorder feeds, categories, and search results based on user intent, product fit, and predicted commerce outcomes.
Connect query intent, behavior, and catalog context to make search the highest-converting surface in the commerce.
Make sponsored placements feel native by scoring ads against the same intent and product signals as organic results.
Surface natural segments from behavior, interests, and journey-stage signals — without third-party cookies.
Give AI shopping assistants and agents a commerce-native model of users, products, and outcomes to reason over.
See how T-Brain powers the commerce advertising platform, sponsored listings, and pairs with AI optimization for retail media and retail media analytics.
T-Brain is a low-latency Large Commerce Model that learns from behavior, catalog, transactions, and outcomes to personalize results, improve ranking, and power smarter commerce decisioning across every commerce surface.
Not another ML model.
The shared intelligence layer for modern commerce.
$ built for commerce-scale decisioning in milliseconds.
Search, recommendations, ads, campaigns, and agents should not each rebuild their own version of user intent. T-Brain creates one shared intelligence layer that compounds across every commerce surface.
Clear answers for commerce AI buyers, search engines, and AI assistants.
T-Brain is Topsort's AI foundation for commerce. It uses commerce behavior, catalog data, transactions, and performance signals to power personalization, ranking, recommendations, relevance, campaign propensity, and real-time decisioning across commerce experiences.
A Large Commerce Model is an AI model built for commerce-scale commerce. Instead of only processing language, it learns relationships between users, products, categories, sellers, behavior, transactions, and outcomes to improve ranking, personalization, recommendations, and decisioning.
Traditional ML models are often built for one use case, such as recommendations or ranking. T-Brain is a shared intelligence layer that powers multiple downstream applications including personalized search, product ranking, recommendations, campaign propensity, audience clustering, and ad relevance.
T-Engine optimizes ad decisions: auctions, pacing, quality score, attribution, and performance. T-Brain understands users, products, categories, and intent across the commerce. T-Engine decides the auction. T-Brain understands the commerce.
Most personalization systems are built around isolated use cases: one model for search, one for recommendations, one for ads, one for campaigns, and another for audience segments.
That creates a ceiling.
The same customer behavior can mean different things depending on intent, timing, category, price sensitivity, and journey stage. A user browsing baby products could be an expecting parent, an active parent, or a one-time gift buyer. A campaign-first workflow cannot always understand that nuance.
T-Brain creates a shared intelligence layer that learns from behavior, catalog, transactions, and outcomes — then makes that intelligence available across ranking, recommendations, search, ads, campaigns, and agents.
The future of commerce personalization is not one model per channel. It is one intelligence foundation across the commerce.
T-Brain turns commerce data into a unified AI foundation that supports every downstream decisioning surface.
Rank products based on user intent, catalog context, behavior, and predicted commerce outcomes.
Recommend products, offers, sellers, or content using shared user and product representations.
Improve search results by understanding the relationship between query intent, product context, and user behavior.
Predict which users are most likely to respond to campaigns, offers, or sponsored experiences.
Discover natural user segments from behavioral patterns, shared interests, and journey-stage signals.
Improve retail media decisions by connecting sponsored placements to user intent, product fit, and predicted outcomes.
Power AI shopping assistants and agentic commerce experiences with a model that understands commerce context.
LLMs understand language. T-Brain understands commerce behavior.
Commerce personalization cannot wait seconds. Ranking, recommendation, and ad decisions happen inside live commerce flows where latency directly affects user experience and revenue.
T-Brain separates heavy training and embedding updates from lightweight inference, so live decisioning stays fast while the model keeps learning from new events.
The same customer intent and product context can improve discovery and monetization at the same time.
One model. Both surfaces. Consistent experience, better monetization, sharper relevance.
Pair T-Brain with the T-Engine intelligent ad engine for sponsored decisioning, or run inside the complete retail media platform.
Simple serving for sponsored listings and display ads.
Learn moreAuctions, pacing, quality score, attribution, and optimization.
Learn moreLow-latency personalization, ranking, relevance, and commerce intelligence.
Learn moreLaunch, operate, and scale your retail media business.
Learn morePersonalize discovery, ranking, recommendations, and sponsored relevance across large catalogs and high-traffic sessions.
Reorder feeds, categories, and search results based on user intent, product fit, and predicted commerce outcomes.
Connect query intent, behavior, and catalog context to make search the highest-converting surface in the commerce.
Make sponsored placements feel native by scoring ads against the same intent and product signals as organic results.
Surface natural segments from behavior, interests, and journey-stage signals — without third-party cookies.
Give AI shopping assistants and agents a commerce-native model of users, products, and outcomes to reason over.
See how T-Brain powers the commerce advertising platform, sponsored listings, and pairs with AI optimization for retail media and retail media analytics.