Silicon Valley is doubling down on defense as geopolitical tensions rise and appetite for modernizing warfare grows. And while many of the startups garnering large valuations are focused on hardware and weaponry — think Anduril, Shield AI, and Skydio — Rune Technologies wants to tackle AI-enabled software for military logistics.
“The U.S. military runs on Excel spreadsheets and white boards and manual processes right now to execute logistics operations,” co-founder David Tuttle told TechCrunch. “Logistics is never the sexiest part of the military. The technology industry emphasis is on how do we make things go boom? How do we build great weapons systems?”
Logistics, Tuttle says, usually falls behind when it comes to innovation. And he should know. Earlier in his career, he was a field artillery officer in the U.S. Army. Later, he served with the Joint Special Operations Command before going on to work at Anduril, where he met his co-founder, ex-Meta Peter Goldsborough. The two founded Rune after seeing how much modern warfare has changed the scale and pace at which armies have to sustain force.
“Ukraine is a sad example of the expenditures of munitions, the consumption of supplies, and those types of things in a near-peer adversary conflict – they will break human-centric and analog-centric processes,” said Tuttle.
Rune’s flagship product TyrOS promises to transform manual logistics processes into intelligent supply webs that predict future needs, optimize current resources, and enable distributed operations – even from a disconnected laptop in the middle of the jungle.
The startup has just raised a $24 million Series A round off the back of pilot deployments under the U.S. Army and U.S. Marine Corps. The round — which Human Capital led with participation from Pax VC, Washington Harbour Partners, a16z, Point72 Ventures, XYZ Venture Capital, and Forward Deployed VC – will go towards expanding TyrOS deployment into other U.S. military services.
TyrOS has two major selling points. The first is its technical capabilities as a mission command system for logistics. TyrOS relies on deep learning models, including time series models, to forecast supply and demand assets like personnel, transportation, equipment, food, and other resources based on hundreds of environmental and supply variables.
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“A logistician thinks about not just, ‘What do I have on hand from supplies?,’ but also, ‘What vehicles do I have to move that?’” said Tuttle. “’What qualified crews do I have to drive that vehicle?’ ‘What routes is that vehicle going to go over?’ ‘And is that threat-informed?’ ‘Is a bridge blown up on the route that we need to reroute around?’”
Tuttle says the team at Rune, two-thirds of which are veterans, is also working to integrate generative AI into TyrOS for “course of action generation,” enabling the system to digest massive datasets in real-time battle space environments so that logisticians and commanders can query it on the fly. And while LLMs have advanced rapidly, TyrOS still relies on traditional mathematical optimization for certain tasks – like planning aircraft loads based on cubic volume and other constraints – where precise calculations are essential.
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