Business Model Airis Labs: How it makes money

Let’s be honest. Most AI startups pitch solutions to problems that do not really keep anyone up at night. Airis Labs is not one of those. This is a company built by people who have actually sat inside intelligence operations, watched analysts drown in hours of raw footage, and decided someone had to fix it. So they did.

How Airis Labs Started: Problem, Solution, and Target Audience

Picture an analyst in a crisis situation. There are drone feeds, smartphone uploads, CCTV recordings, social media clips, and body camera footage all coming in at once. They often lack an index, meaning there is no shortcut system to find the critical information buried inside all that footage. The analyst is doing it manually. It is slow. People die because of that slowness.That is the problem Airis Labs was built to solve.

The company was founded in April 2023 by Noam Friedman, who serves as CEO, Amos Lahav, who oversees US operations, and Rotem Abeles, the Chief Product Officer. All three are in their 40s and previously held senior positions across Israel’s intelligence community and defense-tech ecosystem, including the Prime Minister’s Office, Palantir Technologies, and several cybersecurity companies. These are not first-time founders who read about defense on a blog. They lived this problem.

The platform Airis built turns video and imagery from smartphones, social media, digital forensics, security cameras, body cameras, drones, and other sources into structured intelligence for government agencies. Their target audience is specific: Homeland Security agencies, law enforcement, and military intelligence organizations. Not everyone. The right people.

Competitive Advantage

Here is the thing about defense-AI companies. Most of them build in a lab, present a clean demo, and then struggle when real-world footage is blurry, corrupted, or captured at weird angles by a scared soldier. Airis took a different path entirely.

Within months of founding, the startup deployed its platform into live operations, improving its neural network with low-resolution recordings from global flashpoints, extracted from mass media following international crises. They did not wait. They shipped into chaos and learned from it.

The result? The platform can speed up traditional video analysis tasks by a factor of 150. Read that again. One hundred and fifty times faster.

And it works across everything. The platform can work with video and imagery from the sources a customer is already allowed to use, including body cameras, drones, aerial sensors, CCTV, vehicle cameras, and publicly available open-source video. No ripping and replacing existing infrastructure. No painful migrations. It plugs in and works.

The smarter competitive move, though, is in how they named their category. Airis Labs calls its approach “User-Generated Field Intelligence,” which it says differs from traditional video analytics, open-source intelligence, and general data fusion. By owning a category name, they sidestep direct feature comparisons with bigger competitors. Smart founders know that whoever names the category often wins it.

Marketing Techniques

Most startups blast press releases from day one. Airis did the opposite. It went dark for over two years. No website noise, no conference booths, no LinkedIn thought leadership posts. Just work.

Airis Labs spent the past two and a half years operating in stealth before emerging publicly with a fully loaded announcement that made the whole defense-AI world pay attention at once. That is a deliberate strategy. You show up with receipts, not promises. But stealth alone does not close government contracts.

The company has been selected for the Oracle Defense Ecosystem, which gives them a direct path into procurement conversations that would otherwise take years to crack open. And Airis Labs has joined the US Army acceleration program, which adopts commercial innovations in federal defense. These are not vanity partnerships. They are distribution channels dressed up in institutional clothing.

The investor roster also does marketing work that money cannot directly buy. Backers include Eyal Waldman, Jeff Horing, Yasmin Lukatz, and David Chinn alongside institutional investors PSG Equity, TLV Partners, and Stepstone Group. In defense circles, who backs you signals whether you are worth a meeting. Full stop.

And then there is the oldest marketing technique in the world: results. Airis has deployed systems to multiple security agencies. Every live deployment becomes a reference call for the next deal.

How Airis Labs Makes Money

Simple, actually. Airis Labs offers enterprise solutions to federal governments, intelligence agencies, and customs operations globally via a subscription model.

Recurring revenue from government clients is about as sticky as it gets. Once an agency has integrated a platform into their operational workflows, ripped out their old tools, and trained their analysts, the switching cost is enormous. So the retention is naturally high without Airis having to earn it back every year.

The reality is, government contracts also tend to grow. Agencies expand deployments, add users, and bring in adjacent departments once the first rollout proves itself. That expansion revenue compounds quietly in the background.

Market Share of Airis Labs

Let’s be straight about this. Airis Labs is new. It does not own a dominant share of anything yet.

The competitive set is significant. Palantir’s Project Maven remains the headline US defense-AI deployment for video analysis. Helsing sits at the European end of the same arc with a broader battlefield-AI scope. Anduril, Scale AI’s defense unit, and a clutch of newer Israeli startups including BlueGreen Vision and ION-X compete on overlapping ground.

But market share is a lagging indicator. What matters in early-stage defense companies is positioning and access. And on both counts, Airis has punched well above its weight. Its Oracle ecosystem inclusion and US Army program participation put it inside rooms that most two-year-old startups never enter.

The startup plans to double its headcount by the end of 2026, which tells you they are not in conservation mode. They are going after market share aggressively.

Business Model Canvas of Airis Labs

Key Partners: Oracle Defense Ecosystem, US Army acceleration program, PSG Equity, TLV Partners, intelligence agency clients across the US and allied nations

Key Activities: AI model training on genuine field footage, platform development, navigating government sales cycles, integrating with existing agency infrastructure

Key Resources: A team led by seasoned experts from Palantir, intelligence agencies, and AI/ML fields, $60 million in capital, and proprietary models trained on real operational data

Value Proposition: A unified platform that combines multiple video feeds into a single searchable view, with AI capable of extracting key details from video, audio, and text, eliminating the need for analysts to juggle multiple disconnected tools

Customer Relationships: Long-term government contracts, embedded operational teams, high-touch support for agency clients

Channels: Direct government sales, ecosystem partnerships through Oracle, US Army accelerator access, investor-facilitated introductions in the defense community

Customer Segments: Homeland Security agencies, law enforcement, and military intelligence organizations

Cost Structure: R&D and model training, specialized engineering talent, security certifications and compliance costs, dual operations across Washington D.C. and Tel Aviv

Revenue Streams: Annual subscription licenses, professional services for deployment and integration

Conclusion: Is Airis Labs a Viable Business?

Here is the kicker. Airis Labs has done in three years what most defense startups spend a decade attempting. Founded in April 2023, it now employs around 50 people across Tel Aviv and Washington D.C., has live deployments with multiple government agencies, and has raised $60 million from people who deeply understand how defense procurement actually works.

The risk? Real. Government sales cycles are brutal. Budget cuts happen. Compliance requirements shift. Big competitors like Palantir have relationships baked in over decades, not months.

But the opportunity is equally real. The volume of visual data in every modern conflict or security operation is only growing. Analysts are not. So the gap between what humans can manually process and what actually needs to be reviewed widens every single year. Airis is betting the entire company on closing that gap with software.

And you know what? That is a bet worth making. Not because it is easy. But because the problem is undeniably real, the team has lived it firsthand, and the early traction suggests the product actually works in conditions that would break most demos.

The reality is, most startups fail because they solve imaginary problems. Airis Labs is solving one that costs lives when left unsolved. That is a very different kind of business to be building.

Airis Labs Raised $31M