Airis Labs Raises $31M Series B to Turn Fragmented Video Into Mission-Ready Intelligence

AI defense technology company Airis Labs has raised a $31 million Series B round as governments and intelligence organizations increasingly struggle to manage the overwhelming flood of visual data generated across modern operations. The funding round was led by PSG Equity, with participation from existing investors including TLV Partners, Stepstone Group, Redseed Ventures, and several strategic angel investors. The company says it has now raised $60 million in total funding since its founding in 2023.

The Washington D.C.-based company is focused on a growing challenge inside defense and intelligence environments: massive quantities of video and imagery are now being captured from smartphones, drones, CCTV systems, body cameras, social media platforms, and digital forensic tools, yet most of that information remains difficult to search, analyze, or operationalize in real time.

Airis Labs is attempting to address that problem through a video-first AI platform designed to transform fragmented visual feeds into structured intelligence that analysts, investigators, and AI systems can search, reason over, and act upon.

The Growing Problem of Unstructured Visual Data

Modern intelligence and security operations increasingly rely on visual information collected across decentralized systems. However, while the amount of available footage has grown exponentially, the ability to process it has not kept pace.

Many agencies still depend heavily on human analysts to manually review large quantities of video, images, and field footage. In high-pressure environments, that can create operational bottlenecks where important signals are buried inside enormous volumes of unstructured data.

Airis Labs says its platform is designed to convert that visual information into machine-readable intelligence. Rather than simply storing video feeds, the system attempts to identify contextual information such as what happened, where events occurred, what changed, and what may require further human review.

The company refers to this emerging category as “User-Generated Field Intelligence,” positioning it as distinct from traditional video analytics or open-source intelligence platforms. The idea is to unify fragmented visual sources into a searchable operational layer that can support both analysts and AI-driven workflows.

According to the company, the platform can ingest data from sources including smartphones, social media, body cameras, drones, digital forensic systems, full-motion video streams, CCTV infrastructure, and customer repositories.

AI Systems Designed for Operational Environments

Unlike many AI companies that develop products primarily within controlled testing environments, Airis Labs says its technology was shaped through early field deployments under real operational conditions.

The company states that within months of its founding, its platform was already being used in environments involving fragmented video feeds, massive data volumes, and time-sensitive decision-making.

That deployment-first approach appears central to the company’s positioning. In operational intelligence settings, reliability and contextual understanding often matter more than benchmark performance or narrow object-recognition capabilities.

Rather than focusing exclusively on traditional video analytics tasks such as motion detection or object classification, platforms like Airis Labs are attempting to build systems capable of semantic understanding across visual environments. That includes identifying relationships, anomalies, changes over time, and operationally relevant context within large-scale imagery and video streams.

This broader shift reflects how AI is increasingly being deployed across defense and security infrastructure. As visual data volumes continue to expand, organizations are looking for systems capable of helping analysts prioritize relevant information faster rather than simply collecting more raw data.

Defense AI Investment Continues to Accelerate

The Airis Labs funding round comes amid growing investor interest in defense-focused AI infrastructure and intelligence technologies.

Governments worldwide are rapidly expanding their use of AI systems across surveillance analysis, situational awareness, cyber operations, autonomous systems, and intelligence workflows. In many cases, the challenge is no longer access to information, but the ability to process and interpret it quickly enough to support operational decision-making.

Airis Labs was also recently selected to join Oracle’s Defense Ecosystem initiative, which supports companies developing AI and cloud technologies for government and defense deployments.

The company’s leadership team includes individuals with backgrounds spanning national security operations, intelligence work, enterprise technology deployments, and government-focused field operations. Airis Labs says those operational experiences helped shape the platform around the realities of fragmented, chaotic, and fast-moving field environments rather than idealized laboratory conditions.

Today, the company employs approximately 45 people across operations in the Washington D.C. area and Tel Aviv.

Moving Beyond Traditional Video Analytics

The rise of multimodal AI systems is reshaping how organizations think about visual intelligence. Earlier generations of video analytics platforms often focused on narrow detection tasks, such as identifying objects or triggering alerts based on predefined rules.

Newer systems are increasingly attempting to understand context and relationships across large-scale visual environments. That evolution is becoming particularly important in intelligence and defense settings where analysts may need to review thousands of simultaneous data streams across multiple operational theaters.

Airis Labs argues that the next generation of government AI systems must be capable of understanding the physical world in ways that go beyond simple image recognition. The company says its AI infrastructure is intended to help analysts and operators surface meaningful insights faster while allowing human teams to focus on higher-level judgment and decision-making.

The newly raised capital will be used to expand U.S. operations, grow the company’s workforce, and accelerate development of its intelligence platform as demand for AI-driven operational systems continues to grow across government and defense sectors.