Smack Technologies’ AI Wearable Scores $61M and Pentagon Momentum

Smack Technologies’ AI wearable secured $61 million in a Series B round, and the context behind that capital matters as much as the amount. Per Reuters, the Defense Department’s March 2026 decision to designate Anthropic as a supply-chain risk sent military branches searching for alternative AI vendors, and that institutional scramble created real commercial momentum for startups like Smack.

The California-based company, co-founded by Andy Markoff, Clint Alanis, and Dan Gould per Smack Technologies‘ own website, is building two products in sequence. Its Omega software processes battlefield data through AI models; its Alpha device puts those processed outputs on a screen worn on the operator’s forearm, readable the way a quarterback glances at a play-call sleeve. Markoff, a former Marine Raider, argues that wrist-worn access beats helmet-mounted optics in the field: optical displays that fog in humid environments create more problems than they solve, and a forearm screen sidesteps that entirely.

What Alpha Is Designed to Solve

The Smack Technologies AI wearable addresses a specific challenge that Markoff acknowledges is harder than building the hardware: encoding enough commander’s intent into the device that a disconnected operator can still make sound, contextually informed decisions. The model has to run with little or no connectivity, carrying objectives, unit constraints, and context about adjacent forces directly on the device.

Markoff told Military Times the goal is to decentralize command and control without surrendering tactical coherence, giving the operator enough information to act without waiting on orders from miles away. The device is not meant to make decisions autonomously; it is meant to make the operator’s decisions faster and better-informed.

Alpha has been in development for roughly four months. Markoff projects a working prototype within the next year and contract awards within two years, timelines that are aggressive for defense hardware, where the prototype-to-production pipeline routinely runs long.

Contracts and the Case for the Smack Technologies AI Wearable

Two data points carry the bull argument. In July 2026, Smack announced prototyping contracts from both the Joint Fires Network and the Marine Corps Warfighting Lab, with a combined value exceeding seven figures, per Reuters. Securing those agreements before the hardware prototype is complete suggests the military is backing the team’s concept, not waiting to evaluate a finished product.

The Anthropic supply-chain risk designation also created a structural tailwind rather than a one-time event. Military branches that relied on a short list of major AI providers now have institutional reasons to cultivate early relationships with startups. Smack’s edge-inference design, running models locally on the device rather than routing data through centralized servers, fits both the Pentagon’s operational security requirements and its current need to diversify its vendor base.

The Series B brings Smack’s total capital raised to more than $93 million. A prior Series A raised $32 million, led by Geodesic Capital and Costanoa Ventures with participation from Point72 Ventures, Felicis, and several other investors, per a PR Newswire release. The Series B valuation was not disclosed.

Where the Risk Sits

For the Smack Technologies AI wearable, execution risk is real. Smack built Omega first because software allowed the team to train models against real operational patterns before committing to hardware. Alpha changes the problem: a ruggedized, low-power device running reliable AI inference in austere environments with degraded connectivity is not a software iteration.

Several competing approaches, including helmet-mounted displays and tablet-linked systems, are pursuing the same budget conversations. Smack’s wager is that form factor and connectivity resilience ultimately win out, and the Marine Corps Warfighting Lab contract is evidence that at least one evaluator finds that argument credible.

If the prototype holds up under field testing, the contract pipeline becomes self-reinforcing. If the edge-inference models underperform in live conditions, those prototyping wins look like options rather than commitments. The two-year contract timeline Markoff projects is the figure that decides this thesis from here.