Scout AI, a defense-focused startup founded by Colby Adcock and Collin Otis, just closed a $100 million Series A round to scale its military AI platform called "Fury." The company is training autonomous all-terrain vehicles (ATVs) on a California military base to operate in unpredictable combat zones, marking a significant shift in how the U.S. military approaches autonomous systems.

This isn't just another robotics company chasing venture capital. Scout is one of 20 autonomy companies whose technology is being tested by the U.S. Army's 1st Cavalry Division during regular training cycles at Fort Hood in Texas, with expectations that proven products will be deployed in 2027. The company has already secured $11 million in military technology development contracts from DARPA, the Army Applications Laboratory, and other Department of Defense customers.

What Makes Scout AI Different From Other Defense Tech Startups?

Scout's approach centers on a relatively new AI architecture called Vision Language Action models, or VLAs. These models, first released by Google DeepMind in 2023, combine the reasoning capabilities of large language models (LLMs) with the ability to control physical systems like robots and vehicles. The technology has already seeded robotics startups like Physical Intelligence and Figure AI, the humanoid robot company led by Adcock's brother, Brett.

Colby Adcock sits on Figure's board, and he credits that experience with convincing him that broader intelligence could transform military autonomous vehicles. His brother introduced him to Otis, who was advising Figure, and together they began applying cutting-edge AI techniques to defense challenges.

"If I handed you the controller of a drone right now and I strapped a headset on you, you could learn to fly that thing in minutes. You're actually just learning how to connect your prior knowledge to these couple little joysticks. It's not a big leap. That's the way to think about VLAs and why they're such an unlock," said Collin Otis.

Collin Otis, CTO at Scout AI

The key difference between Scout and traditional autonomous vehicle companies is that Scout's vehicles learn from human drivers in real-world conditions. At a training facility called Foundry, located on the military base, drivers spend eight-hour shifts navigating challenging terrain including steep hills, loose sand, and confusing intersections. The system logs where human drivers had to take over control, then uses that data through reinforcement learning to improve the AI model.

How Is Scout Training Its AI for Combat Conditions?

Scout's training methodology differs significantly from civilian autonomous vehicle development. Rather than operating in structured environments with clear rules, the company's ATVs must learn to navigate unpredictable, off-road terrain that mimics contested battlefields. The company has been training its models using these ATVs for just six weeks after initially using civilian vehicles.

During testing, the autonomous vehicles demonstrated behaviors that suggest genuine learning rather than simple pattern matching. The vehicles hug the right side of wider trails but stay in the middle on narrow ones, mirroring the behavior of their human training drivers. When confused, they slow down to reconsider their next move, a behavior that emerged from the training process rather than explicit programming.

Scout's CTO compared the company's approach to training soldiers, starting with a base level of intelligence and then teaching the system to become what he calls "an incredible military AGI," or artificial general intelligence, rather than just a broadly intelligent system.

Steps to Understanding Scout AI's Military Applications

• Logistics First: Scout's initial focus is on automated resupply missions, where autonomous vehicles carry water, ammunition, or other supplies to distant observation posts, reducing the need for human soldiers to expose themselves to danger.
• Command and Control Software: The company's first widely-adopted product will be called "Ox," a command and control system that allows individual soldiers to orchestrate multiple drones and autonomous ground vehicles using natural language prompts like "Go to this waypoint and watch for enemy forces."
• Autonomous Weapons Development: Scout is also practicing with drone systems for reconnaissance and defense, developing a system where groups of munition drones fly with a larger "quarterback" platform that provides computational resources to coordinate their actions and potentially attack targets without human intervention.

The company's vision extends beyond ground vehicles. Scout is working on a system where multiple drones could search a geographic area for hidden enemy assets and engage them, possibly without human intervention. This represents a significant escalation in autonomous military capability.

Why Does Scout AI's Funding Matter for the Defense Industry?

The $100 million Series A round, led by Align Ventures and Draper Associates, signals serious institutional confidence in Scout's approach. This follows a $15 million seed round in January 2025, bringing total funding to $115 million in just over a year.

What makes this funding round particularly significant is the timeline. Scout expects its first products to be widely adopted by the military, with the company's technology already being tested by active Army units. The expectation is that proven products will be deployed during the 1st Cavalry Division's next deployment in 2027.

Stuart Young, a former DARPA program manager who worked on ground vehicle autonomy, noted that while VLAs are new enough that no company has deployed them operationally yet, "the technology is good enough to be doing that experimentation in the field with soldiers to figure out how to most be effective to U.S. forces".

"The technology is good enough to be doing that experimentation in the field with soldiers to figure out how to most be effective to U.S. forces," said Stuart Young.

Stuart Young, Former DARPA Program Manager

Young recently left DARPA to join Field, another autonomy company in this space. He previously managed a program called RACER that asked companies to create high-speed, autonomous off-road vehicles, helping establish the competitive landscape that Scout now operates within.

The broader context matters here. Scout is not alone in pursuing military autonomy, but its approach using VLAs represents a different technical path than some competitors. The company sees itself primarily as a software company building an intelligence layer for military machines, rather than manufacturing the vehicles themselves.

An active duty infantry officer doing a military fellowship at Scout, Brian Mathwich, recalled a recent exercise in Alaska where he led a resupply convoy in total darkness and wished for autonomous vehicles to help manage the logistics. Scout's technology directly addresses this real operational need.

The convergence of advanced AI architecture, military funding, and near-term deployment timelines suggests that autonomous military systems are moving from research projects to operational tools faster than many observers expected. Scout AI's $100 million bet reflects confidence that this transition is not just possible, but imminent.