Airis Labs emerges from stealth mode with $60 million in funding and a proposal focused on video intelligence for defense agencies.

      The defence-AI company founded in Tel Aviv has secured $31 million in a Series B funding round led by PSG Equity, bringing its total funding to $60 million as it expands its operations in the US from Washington DC. Airis Labs, the stealth-mode defence-AI startup that has spent the last two and a half years under the radar, publicly announced on Tuesday that it has reached a total of $60 million in funding, including the $31 million Series B led by the US growth-equity firm PSG Equity.

      This funding round also includes contributions from TLV Partners, Stepstone Group, Redseed Ventures, and angel investors such as Eyal Waldman, the co-founder and former CEO of Mellanox, which was acquired by Nvidia for approximately $7 billion in 2020. The company's focus is more specific than the broad "AI for defence" category that many startups have been using to secure funding.

      Airis develops what it describes as a video-first intelligence platform: software that processes fragmented visual data, including security camera footage, drone videos, body camera recordings, smartphone uploads, social media images, and what it refers to as "user-generated field intelligence," producing structured, machine-readable outputs that can be queried, analyzed, and acted upon by analysts and AI agents.

      The company positions itself distinctly from traditional video analytics, open-source intelligence platforms, and generic data fusion tools. According to its own estimates, its customer base consists of government agencies around the globe, with an inclusion in the Oracle Defense Ecosystem.

      The issue Airis aims to tackle is significant and well-known within the defence-AI community: government investigators and military intelligence units are overwhelmed by unstructured visual data. An average investigation of an urban incident can yield thousands of hours of mixed-source video, and a typical archive from a drone mission might contain terabytes of unindexed footage. Human analysts cannot sift through such vast amounts of data quickly enough to identify operationally important signals before they become outdated.

      Airis is committed to developing software that transforms this raw visual influx into searchable, structured intelligence. The competitive landscape is notable and includes several key players: Palantir’s Project Maven is a prominent US defence-AI initiative focused on video analysis, while Helsing represents the European counterpart with a broader battlefield-AI focus. Anduril, Scale AI’s defence division, along with several emerging Israeli startups like BlueGreen Vision and ION-X, are also competing in overlapping areas. Airis claims a unique advantage, stating that its platform was designed in actual operational settings from the outset, rather than being developed in a research lab, which they suggest results in a more cohesive user experience and workflow integration compared to their competitors.

      The company's background is noteworthy. Founded in 2023 in Tel Aviv by Noam Friedman (CEO), Rotem Abeles (CPO), and Amos Lahav (CBO), the team comprises individuals with experience from Palantir, Meta, the Israeli Unit 8200 intelligence community, and the wider Israeli AI industry.

      PSG Equity, the firm that led the investment, is also significant. Established in 2014, it has invested in over 130 software and tech-enabled businesses and operates in various cities including Boston, Kansas City, London, Madrid, Paris, and Tel Aviv. Rotem Shacham, a PSG director who led the Airis investment, previously held a position at Viola Ventures and has a background in Unit 8200, which is similar to many members of Airis’s founding team. Thus, their fit on the capital table is understandably close.

      However, Airis Labs has yet to reveal answers to standard inquiries typically associated with a stealth-exit defence-AI announcement, such as which specific government agencies are its customers, what its revenue run-rate is, and how its product measures up against identified competitors in operational tests. The company states that it is operational within government organizations worldwide and that its platform has been validated by the analysts using it rather than by conventional benchmarks. Although this reflects a considered approach on the qualitative aspect, it raises concerns on the transparency of procurement disclosure. The next 18 months will provide clarity on this matter.