Whitepapers
Research and analysis for defense decision-makers.
Technical depth on the operational, architectural, and acquisition questions behind edge AI, mesh ISR, and tactical device management.
Edge AI hardware in 2026: M4, Snapdragon X2, and Jetson Thor compared for tactical inference
Three chipsets define edge AI in 2026. Apple M4 at 38 TOPS for the carry-on command node. Snapdragon X2 at 80 TOPS for ruggedized tablets. Jetson Thor at 2,070 FP4 TFLOPS for base stations. This paper compares memory budgets, thermal profiles, model fit, and practical loadout planning by device class.
Hormuz and the 95% drop: what a real strait closure means for disconnected operations
The Strait of Hormuz has been functionally closed since February 2026. Transit dropped to 5% of normal volume. US forces are in active combat with kinetic and electronic denial layered on top of each other. This paper examines what the Hormuz crisis means for edge AI architecture, maritime mesh, and classification-aware data handling in a real shooting war.
Gemma 4 12B and the end of single-purpose edge models
Google released Gemma 4 12B on June 3, 2026. It handles text, image, and audio in a single encoder-free architecture that fits in 8GB at 4-bit quantization. Apache 2.0 licensed. This paper covers the architecture, memory impact across device tiers, and what it changes for tactical mission loadouts.
Ephemeral missions: how disposable mission data restores operator trust without compromising intelligence
Every device an operator carries is a potential discovery item. Enterprise platforms treat total data capture as a feature. Operators treat it as a liability. Ephemeral missions flip the default: isolated encrypted containers, selective AAR export, cryptographic destruction via hardware secure enclave, and destruction receipts. The team gets the intelligence. The raw data does not survive.
Field biometrics and AI-powered mission readiness: wearable data as a force multiplier
Every operator wears a WHOOP, Garmin, or Apple Watch. The data sits on their phone and goes nowhere useful. This paper covers how to aggregate wearable biometrics, score readiness with on-device AI, and publish the result in ATAK before step-off. No data leaves the network. The medic gets individual status. Command gets a quantifiable go/no-go.
AirBridge: autonomous drone-assisted mesh for tactical data reachback (R&D concept)
R&D concept paper. A drone is more than an ISR asset. At the right altitude, it becomes a temporary airborne mesh bridge, store-and-forward courier, and reachback handoff point. This paper works through the range math, operational value, and routing model behind the AirBridge concept.
The cost of battlefield AI: why localized compute on consumer hardware is the only model that scales
Cloud AI inference costs are rising 30-40% per model generation. Dedicated GPU hardware for the edge costs $15-25K per node with 6-month procurement timelines. Meanwhile Apple's M5 ships 38 TOPS in a $1,099 laptop and the A19 Pro matches it in a phone. The military that figures out how to run localized consumer AI compute in a coordinated mesh will own the next fight.
Tactical device management: turning 200,000 consumer devices into managed mission nodes
CMMC 2.0 requires 110 security controls across 200,000+ defense industrial base companies. NIST SP 800-124r2 separates MDM from mobile threat defense. No integrated solution handles multi-classification enforcement on consumer hardware with tactical features like RF suppression and duress wipe. This paper examines the gap and what it takes to close it.
AI model governance at the tactical edge: provenance, loadouts, and the auditability gap
DoD adopted five AI ethical principles in 2020. The RAI Toolkit mandates explainability for high-risk decisions. Then the Pentagon banned Anthropic from Maven and forced Palantir to rip out its core AI engine in 180 days. The gap between governance policy and operational tooling is where missions stall and legal reviews fail. This paper proposes a field-deployable model governance architecture.
Bottom-up ISR: why the next generation of tactical intelligence starts at the squad
DARPA's MOSAIC warfare concept, Ukraine's decentralized innovation model, and the FY26 budget all point in the same direction: pushing AI, sensors, and decision support lower in the force structure. This paper examines what ISR at the company level and below looks like without enterprise infrastructure.
Edge AI in contested spectrum: operational requirements for inference under EW denial
Chinese EW installations across the Spratly Islands, Russian GPS denial reducing precision weapon effectiveness by up to 90%, and Iranian autonomous drone production scaling 10x. This paper analyzes how electromagnetic threats drive the requirement for local inference and what that means for system architecture.
Acquisition pathways for edge AI platforms: OTAs, SWP, and the Barrier Removal Board
The March 2025 Hegseth software acquisition memo, the November 2025 acquisition transformation strategy, and DIU's 500+ OTA track record have reshaped how DoD buys software. This paper maps the acquisition pathways available to nontraditional defense AI vendors.