Meet our team

For the last decade, ecommerce innovation has been trapped in the personalization paradigm—recommendations based on history, brittle rule engines, and irrelevant search results. But commerce isn’t static. It’s dynamic, emotional, and situational. The future of commerce belongs to retailers that can understand context—what the shopper wants now, what they’re trying to achieve, and connecting that to business goals.

This is here Large Language Models (LLMs) shine. Unlike traditional search or personalization engines, LLMs are built to understand language, infer intent, and reason about goals. They don’t just match keywords—they interpret meaning. They don’t just recall behavior—they respond to nuance. But general-purpose LLMs can’t deliver contextual commerce out of the box. They’re too slow, too expensive, and too broad.

Cimulate solves this with CommerceGPT—a commerce-optimized LLM platform purpose-built to understand shopper intent and drive conversion. We start by training a lightweight retrieval model on each customer’s product catalog and behavioral data, then enrich it with synthetic shopping journeys generated by distilling commerce-relevant knowledge from large, general-purpose LLMs. This enables us to simulate millions of realistic shopping sessions, test outcomes at scale, and learn what actually converts.

That distilled knowledge becomes the foundation of context-driven results—delivered in real time. As your product catalog and shopper behavior evolve, our models continuously retrain to stay accurate and adaptive.

The result? CommerceGPT doesn’t just respond to what shoppers search—it understands what they meant, and surfaces the content most likely to drive action. The result? Faster, smarter, intent-aware experiences. Content that resonates. Results that drive outcomes. It’s not just the end of personalization – it’s the beginning of contextual commerce.