AI is rapidly moving from content generation into the core of how people shop online, reshaping expectations for discovery, comparison, and decision making. Onton, an AI-native commerce startup previously known as Deft, is positioning itself as a new entry point for product search in this shifting landscape. Backed by fresh funding and fast user growth, the company now aims to move beyond furniture and challenge how consumers navigate everything from apparel to electronics.
Onton’s Funding Round and Growth
Onton has closed a $7.5 million funding round led by Footwork, with participation from Liquid 2, Parable Ventures, 43, and other backers. The new capital brings the company’s total funding to around $10 million, following an earlier $1.8 million pre-seed round secured after more than 300 investor meetings. Since launch, Onton has scaled from about 50,000 monthly active users to more than 2 million, handling millions of searches and AI image generations across its platform.
Rethinking AI for E-commerce Search
Co-founder and CEO Zach Hudson argues that the core problem in e-commerce is no longer catalog size, but how people find what they actually want. He notes that large language models are strong at inferring intent, yet they have not significantly reduced the time it takes shoppers to make decisions, and in some cases have lengthened it as users bounce between retailers, chatbots, and visual platforms. Onton’s bet is that the next wave of AI shopping experiences will be defined less by generic chat interfaces and more by specialized systems that can reason about products, spaces, and trade-offs in a way that feels closer to how people actually shop.
Neuro-symbolic Technology and Conversion Impact
At the heart of Onton’s product is a neuro-symbolic architecture designed to limit hallucinations while delivering more precise and logical results. Hudson says this approach lets the system combine statistical learning with symbolic reasoning, so it can incorporate information from the real world that may not appear in a formal product description. According to the company, this technology has helped Onton convert shoppers at roughly three to five times the rate of traditional e-commerce sites, as users develop more trust in the underlying data and recommendations.
Product Experience Beyond Chat
Onton has built its interface around an infinite canvas experience, rather than relying solely on a chat box. Users can generate images, drag in existing visuals, and lay out products side by side for ideation, including uploading photos of their own rooms and asking Onton to furnish them. The goal is to give customers multiple ways to explore options, even when they are unsure how to describe their preferences with precise text queries.
Expansion Plans and Competitive Landscape
The company initially focused on furniture, but the new funding will support a push into apparel, followed by consumer electronics and other categories. Onton is already building out its catalog for clothing and plans to launch that vertical in the near term, where it will compete with startups such as Daydream, Aesthetic, and Style.ai that are also applying AI to fashion discovery. This expansion comes as major retailers like Walmart and Costco invest heavily in AI-enhanced search, logistics, and marketplace capabilities, signaling that AI-first commerce is moving from niche experiments into the mainstream.
Team Growth and Future Outlook
Onton has grown from three full-time employees in 2023 to a team of ten today, with plans to reach around fifteen by adding engineers and researchers. The company sees its relatively small, technical team as an advantage in iterating quickly on both infrastructure and user experience. With more capital and headcount, Onton aims to deepen its technology stack while scaling its role as a neutral starting point for online shopping across multiple categories.
As AI becomes embedded in every stage of retail, from search to fulfillment, Onton is betting that consumers will gravitate toward interfaces that feel more like creative workspaces than static product grids. By combining neuro-symbolic models, visual canvases, and category-specific experiences, the startup aims to shorten decision cycles and make online shopping feel more intuitive. Its latest funding round gives it room to test that thesis on a larger scale, in a market where both tech giants and emerging players are racing to define the next default way to shop.