Airis Labs Raises $60M to Turn Field Video Into Intel

Airis Labs Steps Out of Stealth with $60M to Redefine How Governments See the Battlefield

For years, the problem facing defense analysts and government intelligence teams has not been a shortage of data — it has been the exact opposite. Drones are flying over contested zones, CCTV networks are blanketing city infrastructure, body cameras are recording every patrol, and social media is flooding platforms with real-time footage from virtually every corner of the globe. The challenge, a deeply frustrating one for the people tasked with protecting national security, has always been the same: how do you make sense of all that fragmented, unstructured visual noise fast enough for it to actually matter? A Washington D.C.-based company called Airis Labs has spent the last two years quietly building what it believes is the answer to that question — and now, with $60 million in total funding secured and its first public emergence from stealth, it is ready to show the world what it has been working on.

Airis Labs announced this week that it has raised $60 million in total funding, anchored by a $31 million Series B round led by PSG Equity. Additional participation came from TLV Partners, Stepstone Group, Redseed Ventures, and a group of strategic angel investors with deep roots in national security and enterprise technology. The funding announcement marks not just a financial milestone but a broader coming-out moment for a company that has, until now, been deliberately operating under the radar — building, testing, and deploying its platform in real operational environments before ever announcing its existence to the public.

At The AI World, we believe moments like this one reflect something important happening across the global AI landscape: that the next frontier for artificial intelligence is not inside the lab but out in the field, where conditions are messy, stakes are high, and the margin for error is effectively zero.

What Airis Labs Actually Does — And Why It Matters

To understand why investors and government agencies are paying close attention to Airis Labs, it helps to understand the sheer scale of the problem it is trying to solve. On any given day, a government intelligence team might be receiving footage from dozens of drone feeds, dozens of different CCTV systems, officer body cameras, and open-source social media streams — all of it in different formats, recorded at different resolutions, capturing different angles, and completely disconnected from one another. An analyst trying to piece together a coherent operational picture from that raw data is, in effect, trying to assemble a jigsaw puzzle with pieces from ten different boxes, under time pressure, with lives potentially hanging in the balance.

Airis Labs has built an AI platform specifically designed to ingest that kind of unstructured visual chaos and transform it into something structured, searchable, and immediately actionable. The platform processes video data from smartphones, drones, social media, CCTV networks, and body-worn cameras, running it through a layer of AI-powered analysis that identifies what happened, where it happened, what changed between frames, what patterns are emerging, and — critically — what requires a human being's judgment rather than an automated response. The output is not just processed video. It is structured intelligence that analysts and AI agents can query, cross-reference, and act on in real time.

The company has given this new operational category a name: User-Generated Field Intelligence. It is a label that captures something genuinely novel about what Airis is building — the idea that the unfiltered, unstructured visual data generated by people, devices, and surveillance systems out in the physical world can, with the right AI architecture underneath it, become a legitimate and highly reliable source of mission-critical intelligence. That reframing alone represents a significant conceptual shift in how defense and public safety organizations think about their data assets.

Founded by Veterans, Built for Real-World Conditions

Airis Labs was founded in 2023 by a team with an unusual combination of backgrounds — national security veterans who understand the operational realities of government intelligence work, alongside enterprise technology leaders who understand how to build software that actually ships, scales, and performs under pressure. That combination has shaped the company's approach in ways that set it apart from a lot of defense-adjacent AI startups.

Most AI companies, regardless of the sector they are targeting, build their platforms in controlled environments. They optimize for benchmark performance, refine their models in clean testing conditions, and then attempt to adapt what they have built to the messier realities of real-world deployment. Airis took a deliberately different approach. According to the company, its platform was operational under genuine real-world conditions within just a few months of founding. That is a remarkably short runway from inception to live deployment, and it speaks to the intentionality with which the founding team approached the build.

This field-first philosophy has also informed Airis Labs' selection into the Oracle Defense Ecosystem, a significant endorsement from one of the world's largest enterprise technology companies. Being part of that ecosystem means Airis will have access to Oracle's defense-grade cloud infrastructure and a broader network of government technology partners — the kind of institutional backing that matters enormously when selling into the public sector, where procurement decisions are slow, scrutiny is high, and trust is hard-won.

The company sells its platform to government and public safety customers on a subscription basis, with pricing structures shaped by the scope of the mission, the volume of data being processed, and the level of support required. It is an enterprise software model that is familiar in the commercial world but still relatively uncommon in the defense technology space, where hardware contracts and large one-time project fees have traditionally dominated.

A Team Built Around Diversity and Deep Expertise

One detail about Airis Labs that deserves more attention than it typically receives in funding announcements is the composition of its team. In an industry — defense technology — that has historically skewed heavily male and has often struggled to attract or retain diverse talent, Airis has made meaningful progress. Women make up roughly 40 percent of the company's overall workforce, and one-third of its board seats are held by women. These are not token numbers. They reflect a deliberate organizational philosophy, and they matter both from an equity standpoint and from a practical one: teams with genuinely diverse perspectives tend to build better products, catch blind spots earlier, and navigate complex stakeholder environments more effectively.

Beyond gender diversity, the team brings together military veterans, AI researchers, enterprise software engineers, and government sales professionals — a cross-disciplinary mix that is exactly what a company operating at the intersection of artificial intelligence and national security needs to succeed. The founding CEO, Noam Friedman, has been direct about what he sees as the core purpose of the platform. Speaking about the mission behind Airis, Friedman has noted that the next generation of AI deployed by government agencies needs to genuinely understand the physical world — not just process images, but understand what happened, where it happened, what changed, what is significant, and what still requires a human to make a call. That framing is important. It positions Airis not as a system trying to replace human judgment but as one trying to dramatically improve the quality and speed of the information human decision-makers are working with.

Currently, Airis Labs employs around 45 people across offices in the United States and Israel. With the fresh $60 million now secured, the company has announced plans to double its headcount before the end of 2025, with hiring focused primarily on engineering, product development, and customer deployment roles. That kind of aggressive growth trajectory signals strong confidence in near-term demand — and suggests the company's pipeline of government and public safety contracts is already building meaningfully.

The Real Competition Is Fragmentation Itself

One of the more candid and insightful things Airis Labs has said about its competitive position is that its biggest competitor is rarely another vendor. Instead, what it most often runs up against is the fragmented, improvised, in-house data science work that government teams attempt to build for themselves. Across federal agencies, municipal public safety departments, and defense contractors, there is a long history of trying to stitch together custom analytics solutions from available parts — a data pipeline here, a computer vision model there, a dashboard built by a contractor who has since moved on. These efforts are rarely without merit. The people building them are often genuinely talented and motivated by real operational needs. But they rarely scale. They are hard to maintain, difficult to update as requirements change, and almost impossible to integrate across the organizational silos that define most government bureaucracies.

Airis Labs' pitch is, in essence, that it has solved the hard version of this problem. Its platform is not a prototype or a proof-of-concept that needs to be adapted before it is useful in the field. It is a production-ready system, deployed and tested in real operational conditions, capable of handling the volume, variety, and velocity of visual data that modern government missions actually generate. For an analyst who has spent years fighting with fragmented tools and inconsistent data pipelines, that kind of production-readiness is not just a nice feature — it is a fundamental change in what is possible.

PSG Equity's decision to lead the Series B is worth noting in this context. PSG has built a strong track record backing enterprise software companies with clear go-to-market strategies and demonstrable product-market fit. Their involvement suggests that Airis is not just telling a compelling story about what AI could do for government intelligence — it is showing results that justify serious institutional capital.

What This Means for the Future of AI in Defense and Public Safety

The emergence of Airis Labs is part of a broader and accelerating shift in how artificial intelligence is being applied to defense, intelligence, and public safety challenges. For most of the past decade, AI's role in these domains was largely experimental — pilots, research programs, and occasional high-profile deployments that generated headlines but rarely translated into the kind of systematic, scalable integration that would meaningfully change day-to-day operations.

That is changing. As the underlying technology has matured, as foundational models have become more capable of understanding visual and contextual information, and as the operational need has become increasingly urgent, a new generation of defense-focused AI companies is moving from the experimental phase into production deployment at scale. Airis Labs is among the most interesting of this new cohort, precisely because its founding philosophy — build for the field, not for the lab — aligns so directly with the realities of what government customers actually need.

At The AI World, we have been tracking the rapid evolution of AI applications across sectors that directly affect how societies are governed, protected, and defended. The category that Airis Labs is defining — User-Generated Field Intelligence — feels like one of those genuinely significant conceptual shifts that will, over the next several years, change how practitioners in defense and public safety think about the relationship between raw visual data and actionable knowledge. The challenge of turning the flood of unstructured footage into structured intelligence has been a known problem for a long time. What is new is that the AI tools now exist to tackle it at scale, and companies like Airis Labs are building the systems to make that translation happen in real time, in the field, where it actually counts.

The $60 million raised, the caliber of investors backing the company, the selection into the Oracle Defense Ecosystem, and the aggressive hiring plans all point in the same direction: Airis Labs is not a startup with a theory. It is a company with a deployed product, a growing customer base, and a clear sense of where the market is heading. For government analysts, public safety operators, and the broader AI ecosystem watching this space, that is a combination worth paying close attention to.