Smack Technologies Raises $61M Series B for Edge AI
Smack Technologies has raised a $61M Series B to build the hardware and AI systems intended to bring military decision support closer to the tactical edge. Costanoa Ventures and First In led the round, with additional new and existing investors participating.
The financing, announced on August 18, 2026, brings Smack's total funding to more than $90M. The money will support hardware development for the Alpha platform, expansion of Smack's models across warfighting domains and functions, and hiring across AI research and engineering.
What happened in Smack's Series B
Smack disclosed the new round in an official company announcement. The company did not disclose a valuation, the full investor roster, individual check sizes, or the precise financing structure, so those details remain open rather than becoming convenient fiction.
The Series B follows a $32M Seed and Series A package announced on March 2, 2026. Geodesic Capital and Costanoa Ventures co-led the Series A, while Point72 Ventures led the initial Seed. The earlier financing supported technical hiring, research and development, and Smack's work with U.S. military customers.
That funding cadence is aggressive for a company founded in 2024, but the two rounds finance different stages of the same operating thesis. Omega addressed command-level planning and decision support; Alpha is meant to move campaign-informed intelligence toward edge environments where bandwidth, compute, and time are constrained.
From command software to edge hardware
Smack describes Omega as a command-level AI stack built around Cage 1.0, a model designed to fuse multimodal data and support planning across strategic, operational, and tactical horizons. The company says Omega is moving into production across multiple U.S. military branches, although that deployment status remains a company-reported claim rather than an independently audited metric.
Alpha shifts the engineering problem. It combines Smack's lighter Diet Cage 1.0 model with proprietary hardware intended for immediate decision making closer to the front line. A model that performs in a well-connected command center is not automatically useful when networks degrade, compute disappears, sensors disagree, and operators cannot wait for the cloud to finish thinking.
That is why the hardware line in the announcement matters. Smack is no longer presenting itself as a software company that happens to sell into defense. It wants to build an integrated software and hardware stack for environments where reliability, latency, security, and operator trust are part of the product rather than procurement paperwork bolted on later.
Why intelligent autonomy is the real bet
Smack uses the term "Intelligent Autonomy" for coordinating distributed forces, weapons, platforms, and autonomous systems toward mission objectives. The company pairs that concept with "Decision Dominance," its language for analyzing multimodal information and turning it into useful decisions faster across military echelons and functions.
Those labels sound polished because defense technology has never met a capitalized phrase it did not want on a briefing slide. The substance underneath is more practical: modern operations generate more sensor data than people can process manually, while contested communications make centralized coordination slower and more fragile.
The valuable boundary is human judgment. Smack's public materials frame the technology around decision support and coordinated autonomy, not the removal of human command. The strongest version of the product helps operators understand more and respond faster without pretending that a model should own every ethical, strategic, or tactical choice.
The founders built from the operating problem
Smack was founded by MARSOC veterans Andy Markoff and Clint Alanis, who brought direct experience with military decision workflows into the company. Smack's current team page lists Andy Markoff as founder and CEO, Clint Alanis as COO and co-founder, and Dan Gould as head of strategy and co-founder.
That background gives Smack credibility with the user problem, but it does not make the engineering easy. The company still has to translate domain knowledge into models, product interfaces, secure infrastructure, deployable hardware, testing discipline, and procurement outcomes. Knowing why a system fails in the field is an advantage only if the product team can keep that failure from happening again.
The Series B will help Smack recruit more AI researchers and engineers while broadening model scope across warfighting functions. The hiring plan signals that the company sees the next constraint as technical depth and deployment capacity, not a shortage of defense AI slogans.
What Costanoa Ventures and First In are underwriting
Costanoa Ventures returns as a lead after co-leading the Series A. Its earlier investment rationale emphasized Andy Markoff's leadership, the team's national-security experience, and the need for faster decision making across complex operations.
First In also moves from prior participant to Series B co-lead. Smack did not name the rest of the new and returning syndicate, which means the round should be described with the precision the announcement allows rather than a recycled list from the Series A.
The investors are underwriting a difficult systems company. Success requires advances across models, simulations, applications, edge compute, hardware integration, security, and government deployment. Each layer creates technical and procurement risk, but the integrated stack can become more defensible if Smack turns field knowledge into reliable products that operators actually use.
What this round signals for defense AI
The Series B reflects a broader shift from defense AI demonstrations toward systems expected to work inside operational constraints. Models still matter, but deployment at the edge forces companies to solve power, compute, networking, hardware, data fusion, security, and human-machine interaction as one connected problem.
Smack now has more than $90M in announced funding and a clear sequence of proof points. Alpha must become deployable hardware, Diet Cage 1.0 must remain useful under constrained conditions, Omega must show durable production value, and new technical hires must expand capability without weakening execution.
Capital cannot settle those questions, but it can buy the time and talent required to answer them. The $61M Series B gives Smack room to build past the briefing slide and into the tactical edge, where elegant models meet ugly conditions and usefulness becomes the only metric that matters.
Defense Tech funding, last 30 days
DevCuration's funding database tracked 11 Defense Tech rounds totaling $1.6B in disclosed capital over the past 30 days. Recent deals we covered:
- Terra Industries Adds $18M, Closes $52M Seed RoundSeed · $18M · Aug 18
- Heaviside Raises $60M Series B, Partners With NammoSeries B · $60M · Aug 13
- Soctera's $4M Seed Financing Backs Cooler RF PowerSeed · $4M · Aug 12
- VisionWave Plans D-Fence Acquisition for AI Defense Push$5M · Aug 10
- McNally Capital Takes Majority Stake in TENICAAug 8
Frequently Asked Questions
What will Smack Technologies use the $61M Series B for?
Smack says it will use the funding to develop proprietary hardware for its Alpha tactical-edge platform, expand model scope across warfighting domains and functions, and hire AI researchers and engineers.
Who led Smack Technologies' Series B?
Costanoa Ventures and First In led the $61M Series B. Smack said additional new and existing investors participated but did not publish the complete syndicate.
How much funding has Smack Technologies raised?
Smack says the Series B brings its total funding to more than $90M. That follows $32M in Seed and Series A financing announced in March 2026.
What is the difference between Smack's Alpha and Omega platforms?
Smack describes Omega as a command-level AI stack for planning across time horizons. Alpha is intended for edge-level decision making and combines a lighter model, Diet Cage 1.0, with proprietary hardware.
Why does edge deployment matter for defense AI?
Edge systems must operate when bandwidth, compute, latency, and communications are constrained. That requires AI models, hardware, security, data fusion, and human-machine interaction to work as one deployable system.
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