Gallatin AI's Navigator Lands DIU Contract for US Army Europe — Agentic AI Moves from Tactical Pilots to Theatre-Level Sustainment Planning
Woody Glier spent the last year watching his company's AI logistics tool get stress-tested in combat training centre rotations — not in a lab simulation, but under the real-world conditions of units preparing for deployment. "Gallatin has spent the last year proving Navigator under the stress and real-world conditions of demanding combat training centre rotations," the company's CEO said this month. That proving period just produced a concrete result.
The Defense Innovation Unit awarded Gallatin AI a prototype contract to bring its Navigator platform to US Army Europe and Africa under the Joint Sustainment Decision Tool programme. The deal puts an agentic AI-powered logistics planning system into theatre-level operations, starting with medical supply coordination and casualty evacuation for the Eastern Flank Deterrence Initiative. It uses machine learning to forecast supply requirements, recommend courses of action, and optimise logistics plans — compressing what currently takes days of manual spreadsheet work into minutes.
Rune Technologies secured a separate $99 million IDIQ contract for its TyrOS predictive logistics platform, creating an enterprise acquisition vehicle for AI-driven sustainment across the joint force.
The DoD's AI logistics market is expected to reach $5.8 billion by 2029, with agentic AI moving from pilot programmes to scaled operational deployments in 2026.
The contract marks a shift from predictive analytics — where AI identifies patterns and flags anomalies — to agentic decision support, where the system generates actionable plans, evaluates trade-offs, and adapts as conditions change. Scale AI is on the team as a named teammate, providing generative AI validation of Navigator's recommended courses of action against mission context during joint planning cycles.
Founded in 2024 and incubated through 8VC's Build programme, the company emerged from stealth in April 2025 with a $15 million seed round led by 8VC, Silent Ventures, and Moonshots Capital. Its founding team includes veterans of Palantir, Scale AI, Amazon, and the US intelligence community — a pedigree that signals it was built to navigate defence procurement from day one, not pivot into it later.
Why agentic logistics matters now
The US military's logistics infrastructure was designed for 20th-century conflict patterns: predictable supply lines, permissive environments, and long planning horizons. Near-peer adversaries have invested heavily in capabilities designed to disrupt those assumptions — long-range fires targeting supply nodes, electronic warfare degrading communications, and anti-access systems denying airlift corridors.
The failed Russian convoy outside Kyiv in 2022 demonstrated that logistics collapse can cripple even a major power operating in its own backyard. If fuel shortages, poor maintenance, and coordination breakdowns can stall a 40-mile armoured column, the vulnerability of extended supply chains across the Pacific or Atlantic becomes a strategic risk, not a tactical inconvenience.
"Logistics is the distribution layer of military power, and it has to move at the speed of the fight," said David Tuttle, CEO of Rune Technologies, whose TyrOS platform won a separate $99 million Army IDIQ contract in June 2026. The contract vehicle allows Army units and joint force partners to deploy TyrOS through streamlined task orders — shortening procurement from months to days.
Rune recently launched Saga, an AI agent built on TyrOS that condenses logistics planning from days into seconds, and an Autonomy Development Kit for coordinating autonomous systems involved in sustainment missions. The company has deployed TyrOS across the 25th Infantry Division, 4th Infantry Division, XVIII Airborne Corps, and the US Marine Corps Warfighting Laboratory.
How Navigator works
The platform blends machine learning forecasting with a generative AI engine that proposes supply chain courses of action. The platform estimates current supply levels, real-time consumption rates, and resupply timelines across multiple echelons. Its AI agents model possible resupply allocations and distribution plans based on current conditions and constraints.
Three core capabilities define the system:
Predict. Machine learning models forecast unit consumption based on mission profiles, operational tempo, and historical patterns — identifying potential shortfalls before they become emergencies and flagging when planned resupply operations will fall short.
Recommend. Optimisation algorithms generate courses of action for convoy routing, load sequencing, and resource allocation in near-real-time. Planners compare options that account for enemy activity, terrain, and asset availability, then adjust as the situation evolves.
Track. Real-time visibility of logistics assets, personnel, and supply chains is presented in a common operating picture that synchronises efforts across echelons. The platform supports operation in degraded communications environments — a design requirement driven by the reality that near-peer adversaries will target communication links.
The two companies are not building the same product. Navigator focuses on the operational-to-tactical resupply problem — the daily calculation of food, fuel, water, batteries, and medical supplies flowing from distribution points to the tactical edge. Rune's TyrOS covers the broader sustainment enterprise — asset visibility, predictive maintenance, and autonomous system tasking across the full supply web. Together they represent a market bifurcation between theatre-level logistics planning and enterprise sustainment management, with both anchored on AI rather than rules-based automation.
Market context: $5.8 billion by 2029
The DoD's pivot toward software-defined logistics is backed by real budget trajectory. Deloitte's 2026 Aerospace and Defense Industry Outlook projects US A&D spending on AI and generative AI will reach $5.8 billion by 2029 — 3.5 times higher than 2025 levels. Agentic AI, in particular, is expected to progress from pilot projects to scaled deployments in 2026 across decision-making, procurement, planning, logistics, maintenance, and administrative functions.
This contract is the third JSDT prototype award, following earlier awards to Air Space Intelligence and Watchtower Labs in February 2026. The DIU's programme structure — prototype contracts that can transition to production awards — is specifically designed to bypass the multi-year procurement cycles that have kept software-defined logistics out of operational units. Agility Prime, the Air Force's eVTOL programme, demonstrated the same model: prototype today, programme of record tomorrow.
The commercial analogue is visible in parallel. Forrester reports that 42% of Fortune 500 companies plan to embed generative AI into procurement processes within two years. Enterprise supply chains are mirroring the same shift from rules-based planning to agentic decision support, driven by the same constraint: manual planning cannot scale to the complexity of modern multi-echelon supply networks.
Competitive landscape
It enters a field with established incumbents — Palantir's Gotham platform, BAE Systems' logistics analytics, and IBM's Watson for Defense — but with a structural difference. Legacy platforms are primarily rules-based analytics layered on existing data pipelines. The generative component produces "what-if" scenarios on the fly, a capability that aligns with the DoD's push for rapid decision-making at the speed of relevance.
Scale AI's participation as a validation layer adds credibility. Its generative AI platform cross-checks recommended COAs, ensuring recommendations are grounded in mission context. This is not a standard subcontractor relationship — Scale AI's validation capability is itself a product differentiator that legacy vendors cannot easily replicate.
What needs to fall into place
The contract is a prototype, not a production programme. The DIU pathway has successfully transitioned capabilities to scale — but it has also produced prototypes that never reached operational deployment. Three questions will determine whether Navigator follows the former path:
Integration with existing systems. It must plug into the Joint Battle Command Platform and Global Combat Support System-Army — legacy systems with decades of technical debt. Rune's TyrOS has already navigated this integration with the 1st Cavalry Division; the company has not yet demonstrated the same.
Data availability in contested environments. Its forecasting models depend on data feeds that may be disrupted in peer conflict. The platform's edge architecture is designed for degraded communications, but reduced data quality directly reduces forecast accuracy.
Scaling from battalion to theatre. Navigator was validated at combat training centre rotations, which are battalion- and brigade-level exercises. Theatre-level sustainment across US Army Europe and Africa covers an area from the Baltic to the Black Sea — an order-of-magnitude increase in complexity.
Gallatin AI's JSDT prototype transition to a production programme of record within 18 months — the standard DIU transition timeline.
Rune Technologies Saga deployment data from ongoing 1st Cavalry Division operations — first public metrics on agentic logistics planning speed vs. manual baseline.
Additional DIU JSDT awards to competitors — the programme's total award count signals whether the DoD is building toward a single logistics AI standard or a multi-vendor ecosystem.
Integration milestones between Navigator/GCSS-Army and TyrOS/JBC-P — legacy system interoperability is the binding constraint on both platforms.
Development scenarios
🟢 Optimistic scenario (25%)
Implications: Agentic AI logistics becomes a standard programme-of-record capability, creating a template for other DIU prototype transitions and accelerating the DoD's broader shift from rules-based to AI-native logistics planning.
🟡 Base-case scenario (55%)
Implications: Agentic logistics AI becomes a persistent programme-of-record capability, but procurement fragmentation limits standardisation. Integration with legacy GCSS-Army remains the binding constraint on both platforms.
🔴 Pessimistic scenario (20%)
Implications: The DoD's agentic logistics transition narrows to a single-vendor path, reducing competitive pressure. Integration with legacy systems proves to be the binding constraint that the DIU prototype model cannot resolve within its standard timeline.
