Databricks, flush with fresh capital from a staggering $5 billion round just closed last month, isn’t sitting still. Already a giant in cloud data analytics, the company is now setting its sights on security, and it’s not coming unarmed. Tuesday brought news of *Lakewatch*, a security platform that fuses Databricks’ capacity to wrangle vast oceans of data with classic SIEM features—threat detection, alert investigation—but filtered through a lens of artificial intelligence. The secret sauce? AI agents built on Anthropic’s Claude.
To build this, Databricks pulled two small but ambitious startups into its orbit: Antimatter and SiftD.ai, snapping them up in quietly executed deals. Antimatter, led by security researcher Andrew Krioukov, was quietly acquired last year, but the purchase came to light only now. Then, with almost reckless speed, Databricks moved to absorb SiftD.ai—a company so fresh, its product had only saw daylight last November. SiftD.ai offered an interactive notebook, something in the vein of a Jupyter notebook, where humans and AI agents could work shoulder to shoulder. What’s almost as interesting as the technology: SiftD’s co-founder and CEO, Steve Zhang, spent years as chief scientist at Splunk, where he developed the influential Search Processing Language. Zhang’s career touched other points of note—he served as CTO at Astronomer (departing in 2023, before its CEO became entangled in scandal).
Details of the purchases? Still murky. For Antimatter, industry chatter points to a $12 million raise in 2022 led by New Enterprise Associates. SiftD, meanwhile, operated in near-stealth. If there was outside funding, it left no trace. Both companies were lean operations: SiftD scarcely a handful of engineers, Antimatter perhaps 50 strong at most. The SiftD hire, clearly, was more about nabbing talent than technology, though Antimatter brought intellectual property along for the ride. Krioukov, for instance, showcased Antimatter’s technology this year at the RSA Innovation Sandbox contest—a “data control plane” that notably let businesses roll out AI agents safely, all the while keeping sensitive data closely guarded.
Databricks has yet to spell out how many new faces have joined its ranks, but confirms both startup teams came aboard. Krioukov is now front and center in leading the Lakewatch effort, steering this new ship inside Databricks’ expanding fleet.
This is just the latest maneuver in Databricks’ long game. The company sees itself as an aggressive and forward-thinking predator in tech’s fast-moving waters. When asked about its acquisition appetite, a spokesperson was candid: “We’re always looking to what’s next. Our goal is to stay ahead of the market and close gaps in what our customers need.” The implication: the shopping spree isn’t over—and Databricks is determined to keep its competitive edge razor-sharp.
Meanwhile, the industry’s calendar is already bristling with anticipation—TechCrunch’s Disrupt conference, set for October, has become a rallying point for the ecosystem’s hungry crowd: founders, investors, tech leaders. Connections forged at these gatherings often spark the next big acquisition or breakthrough. Databricks’ early and fast deals—drawing in nimble teams and cutting-edge ideas—underscore just how much speed and collaboration matter now.
The subtext? Even beyond big headlines and funding totals, the most valuable asset is talent and vision. Databricks, with its deep pockets and relentless ambition, is betting that scooping up small, inventive teams today will yield oversized returns tomorrow. With Lakewatch, it’s not just building a product. It’s stitching together the people, algorithms, and infrastructure to redefine what security means for enterprises swimming in data. In this, Databricks proves it’s more than a platform—it’s a force intent on shaping the future of how information is protected in an AI-driven world.
