Deep Labs

Deep Labs

Founded in 2016 by former Visa and US government technology executive Scott Edington, Deep Labs emerged from the intelligence and payments infrastructure worlds. Edington had previously run Visa's Global Solution Architecture, where he observed first-hand the limitations of device-and-password authentication. The company set up as an independent venture-backed technology firm, not an internal lab, raising capital to build a proprietary system that could score identity risk continuously using behavioral signals. Deep Labs deploys its persona-based decisioning engine across enterprise access, payments authorization and government credentialing. The system ingests how a user interacts with a device — keystroke cadence, mouse movement, swipe pressure — and compares it in milliseconds against a dynamic model of that individual's typical behavior, alongside device, network and environmental signals. In 2019, the firm secured a contract with the US Department of Homeland Security's Silicon Valley Innovation Program to test its technology for border entry and airport screening. A separate proof-of-concept with Visa signaled the firm's ambition to layer behavioral intelligence into payment authorization without adding friction. The company's target set spans financial institutions, government agencies and large-scale enterprise environments where credential theft remains the dominant attack vector. Deep Labs expanded its team across San Francisco, London and Manila, drawing from former US intelligence, financial crime and advanced analytics circles. In March 2021 the firm closed a $16 million Series A led by Gunnar Overstrom at Corsair Capital and Serendipity Capital, with participation from Gramercy Ventures (per Crunchbase, 2021). Later that year, Deep Labs locked a partnership with Lexington, Kentucky-based LexisNexis Risk Solutions to embed the behavioral intelligence engine into LexisNexis's financial crime and identity verification stack (per LexisNexis press release, August 2021). The firm remained private, with no publicly disclosed subsequent rounds. The firm's structural differentiator lies in the adjacency of its government and commercial credentialing credentials. Most behavioral biometrics companies sell either into enterprise fraud teams or into law enforcement; Deep Labs built its reference stack in parallel with both, under procurement standards that require an unusual degree of model transparency. That dual-use architecture — payments and national security — makes its customer validation unusually hard to replicate for venture-stage competitors that lack cleared personnel or government program experience.