The New Defense Post #35

Welcome back to the #35 edition of The New Defense Post!

In this edition, we’ll cover:

On April 24, U.S. Marine Corps Systems Command in Quantico awarded SteelRock Technologies of London a $9,5M urgent-authority contract for NightFighter Mini counter-drone jammer systems and associated spares, under the Marines' Organic-Counter small Unmanned Aerial Systems (O-CsUAS) programme. Delivery is required by August 25 — four months from award. The entire contract value was obligated at award using FY2024 Marine Corps procurement funds. All work will be performed in London. (U.S. DoW Contracts) (defense Blog)

SteelRock Technologies was founded in 2016 by Rupert English, a former UK special operations veteran, and has never raised disclosed VC funding. The company is bootstrapped, staffed with ex-UK Elite Forces personnel, and manufactures in Britain.

The NightFighter Mini — the most compact system in SteelRock's product family — weighs 2 kilograms with battery installed, measures 25 by 15 by 19 centimetres, and is operated by a single Marine as a weapon-mounted or sidearm-carried system. It covers four preset radio frequency bands, including Wi-Fi and military spectrum. Effective range is Visual Line of Sight: if the operator can see the drone, the system can engage it. (SteelRock Technologies)

The VLOS constraint is a genuine limitation: as adversaries shift to pre-programmed autonomous drones that don't rely on live RF links during flight, jamming-only effectors face a growing capability gap. That gap is where the next generation of C-UAS startups should be building.

📰 Our Take: Counter-drone "jamming guns" are considered quite ineffective when it comes to frontline usage. Currently, they aren't used all that much in Ukraine, and they are heavy and expensive.

Needless to say, they are obviously ineffective when there is a last-mile targeting system in place and when the drone has advanced autonomy features.

On April 21, KBR's Mission Technology Solutions division announced a strategic alliance with Tagup, a defense technology company founded at MIT, to integrate Tagup's Manifest platform into KBR's global military logistics operations. Initial deployments target U.S. Army and Marine Corps ground equipment sustainment.

The Manifest platform uses Generative Reinforcement Learning (GRL) to simulate millions of logistics scenarios simultaneously, and output recommended sustainment plans in seconds, with a conversational AI interface that lets operators query trade-offs in plain language. (Globe Newswire) (Executive Biz)

The background figure that makes this announcement significant: the U.S. Defense Logistics Agency currently achieves approximately 60% accuracy in demand planning — meaning four in ten items are either over-ordered or under-ordered against actual need.

Maj. Gen. David Sanford, DLA's director of logistics operations, described the gap publicly in January, noting the target is to push accuracy toward 85%. KBR's Tagup alliance is one of several AI-driven initiatives targeting that gap. (Federal News Network)

🗣 Jon Garrity, CEO, Tagup: "Sustainment at KBR's scale generates enormous decision volume: thousands of competing resource trade-offs, every day, across global theatres. Manifest gives KBR the ability to turn that complexity into a quantitative advantage by continuously modelling the logistics environment, evaluating courses of action against real constraints and surfacing the decisions that protect readiness before problems compound." (Globe Newswire)

📰 Our Take: Tagup is a defense startup that went from MIT to a KBR enterprise alliance covering U.S. Army and Marine Corps logistics. That's a meaningful B2G traction signal, and the platform architecture, GRL plus conversational AI for sustainment trade-offs, is genuinely novel applied to military supply chains.

For European founders, this story points to a gap that's even wider on this side of the Atlantic. European militaries are scaling defense budgets at a pace, but their logistics infrastructure is, if anything, more analogue than the U.S. baseline.

The DLA runs 55 AI models in production and has an AI Center of Excellence. European defense logistics agencies don't have equivalents. The market for predictive sustainment, parts demand forecasting, and maintenance optimisation tools is wide open across NATO allies.

Pentagon Unveils $1.5T FY2027 Budget Request, the Largest in Modern History (Defense News)

A400M Upgraded to Deploy Up to 50 Drones or 12 TAURUS Missiles via Palletised Cargo System (Interesting Engineering)

Australia Releases 2026 National defense Strategy, Signalling Accelerated ISR and Space Investment (USNI News)

Fun fact: the U.S. Defense Logistics Agency, one of the most sophisticated military supply chains on Earth, currently achieves 60% demand planning accuracy. That means roughly four in ten procurement decisions miss the mark, resulting in either stockpiles of parts nobody needs or critical shortages of the ones they do. The DLA manages supply to every branch of the U.S. military across every continent, and it's building 55 AI models in production to close the gap. The target is 85% accuracy. (Federal News Network)

European military logistics starts from a much weaker baseline. defense budgets across the continent are growing at historic rates, but the logistics infrastructure supporting them hasn't kept pace. The platforms are being ordered, but the sustainment systems to keep them operational in a high-tempo conflict are years behind.

That's not a political observation. It's an engineering one: modern defense platforms generate enormous maintenance data, and without predictive tools that can ingest and act on it, readiness degrades faster than any adversary needs to act.

The KBR-Tagup deal, which we cover in Spotlight 3, is a useful model for what the European gap looks like from the other side. Tagup's Manifest platform does three things simultaneously: it simulates millions of logistics scenarios under real constraints, ranks them by feasibility and readiness impact, and exposes the trade-offs via a conversational interface.

That architecture, GRL plus constraint satisfaction plus human-readable outputs, is what it takes to turn a military logistics operation from reactive to anticipatory. The market for AI in defense logistics is valued at $2.73 billion globally in 2026 and projected to reach $5.31 billion by 2030. Europe's share of that market currently has almost no startup-native participants. (Research and Markets)

European NATO members face identical sustainment challenges to the U.S.: parts demand forecasting, maintenance scheduling under personnel and facility constraints, and spare parts inventory optimisation across distributed depots.

The same AI tooling that KBR is deploying for the U.S. Army could be adapted for Bundeswehr ground vehicles, French Army maintenance operations, or the Baltic states' expanding defense infrastructure. The procurement pathway in Europe is harder, but DIANA, EDF sub-calls, and national innovation units like France's AID are all creating on-ramps that didn't exist three years ago. The question is who's building the product.

defense logistics is unglamorous, which is exactly why it's underbuilt. The competitive dynamics of the European defense tech market have so far concentrated capital and talent in strike drones, interceptors, and autonomous platforms. Those are real opportunities, but they're crowded.

For founders with backgrounds in supply chain, operations research, or industrial AI, this is a cleaner wedge into defense than most: the problem is well-defined, the data is available (if you can access it), and the customer has a readiness imperative that doesn't go away.

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