San Francisco-based Onton has unveiled Ontology 1, a new AI model engineered for trustworthy product discovery on the emerging agentic web. This model addresses a critical problem: AI systems increasingly research and execute consumer purchasing decisions, but often rely on manipulated or synthetic information.
Built from scratch, Ontology 1 aims to cut through the noise of incentivized recommendations and fake content. Onton's co-founder, Alex Gunnarson, stated, "Everyone is focused on building smarter agents. We're focused on a different question: what should those agents trust?"
Outperforming Existing Discovery Platforms
Onton claims its model outperforms dominant players like Google Shopping and Amazon in accuracy benchmarks. The performance gap is most pronounced in verifying product information veracity, a domain historically difficult for AI.
For example, an AI agent tasked with finding a sofa under $2,000 might sift through thousands of results, reviews, and influencer posts. Without a reliable way to discern signal from noise, the agent risks recommending products based on untrustworthy data. Onton was built to solve this problem, which the company views as an escalating default state of the internet.
A New Foundation for Agentic Commerce
The modern internet was designed for human evaluation, where intuition and skepticism filtered content. As AI agents take over more decision-making, these human filters disappear, leaving systems vulnerable to manipulation.