Three former Spotify engineers have raised $10 million in seed funding to launch Malachyte, a startup that applies the AI behind Spotify’s recommendation engine to e-commerce, aiming to predict shopper intent in real time rather than relying on past purchases.
The funding round, co-led by Bessemer Venture Partners and Gradient, with participation from Harpoon Ventures, was announced Thursday. Malachyte was founded by Sidd Motwani, Ian Anderson, and Shivaditya Sinha, who previously built the behavioral intelligence infrastructure powering Spotify’s recommendations for over 800 million users.
What is Vector AI and how does it work?
Malachyte’s platform uses a system called “two-headed Vector AI,” which predicts what a shopper wants next and learns their general taste in real time. Unlike traditional personalization that relies on historical purchases or demographic segmentation, this system builds a profile from the moment a page loads, using context such as device type, time of day, and click behavior.
“Our system starts forming before the first click, using the context available the moment the page loads,” said Motwani, CEO of Malachyte, in an interview. “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.”
This approach treats every hover, click, scroll, and search refinement as a live signal, continuously updating the shopper’s profile within a single session. The company claims this allows for a more relevant experience that improves the longer a user stays and on subsequent visits.
Why does this matter for e-commerce?
Most online stores treat first-time visitors with generic storefronts, and returning customers receive recommendations based on what they bought before, not what they need now. Malachyte argues this misses the most valuable customer intelligence available—real-time behavioral signals that indicate current intent.
“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,” Motwani explained. “We read it continuously, so each action makes the user’s vector more confident about both preference and current intent.”
Contextual signals are also underutilized, he noted. “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.”
How Malachyte is rolling out
Malachyte has been developing and testing its technology since 2024, working with more than 20 enterprise customers across travel, grocery, and retail before focusing on e-commerce. Its platform went live in fall 2025 with Fun.com, and since June 2026 it has been available to Shopify merchants through a native integration. Larger retailers can access the technology via API.
The company plans to use the seed funding to scale distribution and hire product and commercial leaders. Looking ahead, Motwani sees a bigger opportunity in unifying merchandising and marketing around the same understanding of customer behavior.
Conclusion
Malachyte’s approach represents a shift from reactive, history-based personalization to real-time, intent-aware systems. By bringing the technology that powers Spotify’s recommendations to e-commerce, the startup aims to make online shopping more responsive to individual needs, potentially improving conversion and customer satisfaction. The seed funding will support its expansion as it seeks to establish a foothold in the competitive e-commerce software market.
FAQs
Q1: What is Malachyte’s core technology?
Malachyte uses a “two-headed Vector AI” system that predicts shopper intent and taste in real time, using behavioral signals like clicks, scrolls, and searches, without relying on historical data or user accounts.
Q2: How is Malachyte different from other personalization tools?
Most tools rely on past purchases or demographic segmentation, updating overnight. Malachyte reads every action continuously, adjusting recommendations instantly within a single session, and considers contextual signals like device and time of day.
Q3: Who are the founders and what is their background?
The founders—Sidd Motwani, Ian Anderson, and Shivaditya Sinha—previously built the behavioral intelligence infrastructure behind Spotify’s recommendation engine, which powers about 90% of recommendations for its 800 million users.
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