Perciv AI, a deep-tech startup from Delft specializing in AI-powered radar perception, announced a €2.5 million seed funding round led by DayOne Capital and Keen Venture Partners, with Vinci Venture Capital also participating. The funding will support the company’s expansion and deployment of its advanced radar perception technology across industries such as automotive, robotics, and aerospace.
Founded by TU Delft alumni Balazs Szekeres, Dr. Andras Palffy, and Srimannarayana Baratam, Perciv AI tackles the high costs of LiDAR sensors and limitations of traditional radar systems. Its proprietary AI-driven radar and radar-camera fusion technology delivers LiDAR-level performance at a fraction of the cost. This innovation enables automated systems, robots, and vehicles to accurately perceive their surroundings under various conditions while remaining compatible with diverse radar types and applications.
DayOne Capital’s Managing Partner, Dr. Csaba Kakosy, emphasized the transformative potential of Perciv AI’s technology, stating that it “not only drives cost efficiencies for OEMs but also paves the way for safer, smarter, and more sustainable mobility across industries.”
Keen Venture Partners, co-lead investors in the round, highlighted Perciv AI’s unique approach. General Partner Alexander Ribbink and Investor Giuseppe Lacerenza expressed confidence in the company’s ability to redefine radar capabilities, calling it “a compelling alternative to LiDAR and cameras” with applications across complex environments.
Vinci Venture Capital’s Investment Director, Aylin Girgin Ozbilis, added that “Perciv AI’s strong market fit and significant interest from automotive and industrial leaders make it a standout innovator in the sector.”
With the new funding, Perciv AI aims to accelerate the adoption of its radar-based solutions, offering a scalable and cost-effective alternative to existing technologies. The company plans to deepen its impact in established industries while exploring emerging use cases for its advanced AI-powered systems.
Featured image. Credit: Perciv AI
