Nima Negahban

Nima Negahban is the CEO and co-founder of Kinetica, a real-time GPU-accelerated analytics database company. Public bios describe him as the original developer and software architect of the Kinetica platform, responsible for the company’s core technical vision. Kinetica originated from work beginning in 2009 for the U.S. Army Intelligence and Security Command and the NSA, where Negahban and co-founder Amit Vij were hired to build a system for real-time threat tracking across large streaming datasets.

Before Kinetica, Negahban developed big-data systems across biotechnology, high-speed trading, and GPU-based analytics as a lead architect and engineer with The Real Deal, Digital Sports, Equipoise Imaging, and Synergetic Data Systems. Earlier in his career, he was a senior consultant at Booz Allen Hamilton. He holds a B.S. in Computer Science from the University of Maryland, and his LinkedIn lists University of Maryland attendance from 2001 to 2005.

Kinetica has raised venture capital from Canvas Ventures, Meritech Capital Partners, Citi Ventures, GreatPoint Ventures, and Ray Lane. In 2017, Kinetica announced a $50 million Series A and $63 million in total venture financing. Negahban has served in technical and executive leadership roles at the company; Kinetica and third-party profiles currently identify him as co-founder and CEO.

As an investor, Negahban’s clearest verified public angel activity is CaryRx/CaryHealth. CaryRx’s Wefunder page listed him as a “Board member / Angel Investor,” describing him as CTO/co-founder of Kinetica and the initial architect of IronNet. CaryHealth’s current site lists him as Board Member & Technical Advisor.

• No standalone public angel-investing thesis was found. The public evidence points to an operator-angel profile: he backs and advises companies where deep technical architecture, AI/data infrastructure, and operational execution matter.
• His verified angel/board involvement with CaryRx/CaryHealth suggests interest in healthcare infrastructure businesses that combine software, fulfillment workflows, and patient experience.
• His Kinetica work indicates a strong preference for systems that solve real-time data problems at scale. Kinetica describes its platform as unifying vector, graph, spatial, and time-series analytics for instant insight across real-time datasets.
• In Kinetica’s 2024 vector-search announcement, Negahban said: “At Kinetica, our focus has always been on delivering real-time insights in a rapidly evolving data landscape through our natively vectorized GPU optimized architecture.”
• In a 2025 post, he framed the “agent retrieval problem” as agents needing access to multiple data types “all in real time,” and positioned Kinetica as a retrieval backbone for AI. This suggests he is likely to understand pitches around enterprise AI only when they are tied to real data, retrieval, latency, and production deployment.