Ex-Spotify Employees Raise $10M to Solve E-Commerce's Conversion Problem With AI

Ex-Spotify employees raise $10M to bring the AI behind its recommendations to e-commerce

Sidd Motwani, Ian Anderson and Shivaditya Sinha spent years building the behavioral intelligence infrastructure behind Spotify's recommendation engine. Called Vector AI, the system is designed to predict a person's intent and next actions instead of relying only on their past behavior. It powers about 90% of Spotify's recommendations to its 800 million users. Now, the three are bringing a similar system to e-commerce with their new startup, Malachyte. The company on Thursday said it had raised $10 million in seed funding to scale distribution and hire more product and commercial leaders. Malachyte was formed from the belief that most online stores treat shoppers the same way: Personalization is largely dictated by historical purchases, demographic segmentation, or logged-in customer profiles. That means first-time visitors often see the same generic storefront as everyone else, while existing shoppers receive recommendations based primarily on what they bought previously rather than what they need today. The startup wants to change that by building real-time, intent-aware shopping experiences. Its platform uses what it calls "two-headed Vector AI" to predict what product a shopper wants next, learn their general taste, and fine-tune continuously based on what they do in real time. "[Our] system starts forming before the first click, using the context available the moment the page loads. Within a single session, we build a real read on both preferences and what someone is trying to accomplish right now," Motwani, Malachyte's CEO, told TechCrunch. "A search for 'heavy-duty boot' followed by two clicks on steel-toed boots is enough to move work pants and gloves up the page and push dress shoes down, with no account or history required. Every additional action sharpens the profile, so the experience gets more relevant the longer someone stays, and again on their next visit." Motwani argues that retailers already possess their most valuable source of customer intelligence, but rarely take advantage of it in real time. "Every hover, click, scroll, search refinement and add-to-cart is a signal, and most systems either never act on it in the moment or aggregate it into a segment overnight. We read it continuously, so each action makes the user's vector more confident about both preference and current intent," he added. He also believes contextual signals remain significantly underutilized. "A phone visitor at 11 p.m. from an email link is in a different state of mind than the same person on a laptop mid-morning, and most systems treat them identically," Motwani said. The company has been developing and testing its technology since 2024, and worked with more than 20 enterprise customers across travel, grocery and retail before ultimately focusing on e-commerce. Its platform first went live in the fall of 2025 with Fun.com. Since June 2026, it has been generally available to Shopify merchants through a native integration, while larger retailers can integrate the technology through its API. Looking ahead, Motwani says the bigger opportunity is in bringing merchandising and marketing together around the same understanding of customer behavior. The funding round was co-led by Bessemer Venture Partners and Gradient, with participation from Harpoon Ventures.

Spotify Vets' eCommerce-Focused AI Startup Raises $10 Million | PYMNTS.com

The company was co-founded by the team behind the behavioral intelligence infrastructure that powers the bulk of Spotify's recommendations and aims to bring the same technology to retail and eCommerce brands, Malachyte said in a Thursday (Aug. 6) news release. "The raise comes as consumer e-commerce faces a conversion problem," the release said. Advances in machine learning-driven ad targeting on Google, Meta, and TikTok "have made audience acquisition more precise than ever, yet the website experience most shoppers meet remains static." At the same time, modern digital personalization stacks can't read shopper context or identify first-time visitors, while customer acquisition and marketing costs continue to rise. "Brands are paying more than ever to acquire customers, then trying to convert them with a stack that only understands the fraction it already recognizes," Malachyte CEO Sidd Motwani said in the release. "Our technology reads behavior instead of logins or cookies, so it understands every visitor before their first click, and keeps sharpening with every action. That's infrastructure built for how commerce works today." The release also cites projections from McKinsey projects that AI agents could orchestrate up to $1 trillion of U.S. retail by 2030, which makes understanding shopper behavior more valuable. "As commerce enters the agentic era, two major forces are converging: consumers have so much less patience when website or search experiences are not tailored to their intent, and agents are increasingly shaping the buyer journey," said Maha Malik, vice president at Bessemer Venture Partners, which led the funding round. "Yet most commerce infrastructure is not built to understand buyer intent in real time, whether that's for a human or an agent. The Malachyte team has spent their careers solving some of the hardest problems in personalization at massive scale making them exceptionally well positioned to help brands meet this much higher bar for relevance." The funding comes as AI continues to become part of mainstream shopping, as research from PYMNTS Intelligence has found. Close to half of all online shoppers turned to artificial intelligence during their most recent buying journey, according to "Global Digital Shopping Index: The AI-Powered Shopper Has Arrived." The same report found ChatGPT quickly becoming a major product research tool, with usage jumping from 2% to 30% in a two-year span. "Consumers are also looking ahead: 64% expect to use AI shopping agents within two years, especially for tasks such as comparing products, managing loyalty programs and handling returns," PYMNTS wrote.