Strategy first: how Puget Systems 3.1×'d AI revenue in nine months
The situation
Puget Systems is one of the most respected custom-workstation builders in the world, and a go-to choice for film, gaming, and creative professionals who need serious local compute. By 2025 the AI demand signal was unmistakable, but the company had no dedicated AI go-to-market function, and its AI software product was still an idea rather than a release. Puget was built for hardware excellence; AI go-to-market was a different muscle. Puget's president brought in Clear Mirror to lead AI strategy and business development.
Strategy before product
The instinct is to start building. The constraint wasn't the product. In the first thirteen days we reviewed the data, aligned the executive team, and got an AI go-to-market strategy approved. It was built on Clear Mirror's core philosophy: augmentation, not replacement. Much of the industry was selling AI as a way to need fewer people. Puget's customers, from creators to consultants to builders, wanted the opposite: tools that amplify their own skills, running on hardware they own, with full privacy and control of their work.
That positioning started where the brand already had trust: the film and gaming creators who made Puget's name. It also fit the customers already arriving, entrepreneurs from finance, construction, intelligence, and robotics who need powerful local compute.
Three moves, in order
1. Rebuild the funnel around the user's journey. We reoriented Puget's AI web presence around what customers are trying to do rather than hardware specs, in the develop, deploy, scale structure now live at pugetsystems.com/solutions/ai.
2. Spread the fluency. We brought AI fluency to everyone who touches a customer, so the people closest to the buyer could match a use case to the right hardware and carry the strategy themselves.
3. Then ship the product. With the funnel live and the team fluent, we worked alongside Puget's engineers to ship App-Packs: pre-validated open-source stacks that take a customer from unboxing to a working AI environment. Concept to shipped product took five months, landing in a funnel and a sales motion built to receive it.
The results
Demand was already rising when the engagement began; the first month spiked before any of this could land. The work was never to conjure demand. It was to make Puget able to capture and compound it, and that's the difference between a spike and a trendline.
Over the first nine months, Puget's AI product revenue grew to roughly 3.1x its pre-engagement run rate, comparing quarterly averages from Q3 2025 to Q2 2026. AI's share of monthly revenue more than doubled over the same window.
We audited attribution and report the conservative figure, not the first one we measured.
And it wasn't a rising market lifting all boats: the rest of the business grew too, but most of Puget's revenue growth came from AI.
What lasted
The strategy is still running, and Puget runs it. The "Edge Cloud" positioning we introduced is now how Puget and its partners describe the category. The team now teaches, sizes, and sells AI on its own. That's the part we're proudest of: not the number, the capability that stays.
Revenue figures are indexed to the pre-engagement baseline (Q3 2025 quarterly average) and verified against internal sales data; the vertical scale is withheld.