We began in 3D visualization, where studios, animators, and ArchViz teams needed massive bursts of compute power without waste. Rendering was our proving ground: deadlines were tight, budgets were real, and the demand for scale came in unpredictable waves. We learned how to route workloads to the right capacity at the right moment, often prioritizing greener data centers, and we built the discipline to do it reliably.

That experience shaped the DNA of Helio. It taught us how to deliver compute as a fluid resource, not a fixed asset. And it set the stage for where we are today: helping companies solve the same challenge in an even bigger arena.

After a surge of funding for AI startups, reality is setting in. Unit economics will decide who endures. GPU costs rise fast, cloud capacity swings, and scarce engineering time disappears into infrastructure work. The risk is simple to state and hard to avoid: scale can become a straight line to unprofitability.

Helio exists to change that trajectory. We are applying what we learned in 3D visualization to AI training, inference, and batch jobs. The Helio Core, our Swiss-built platform, matches global compute capacity to demand and routes each job to the best fit for performance, price, and location. Startups and companies get cost-efficient pricing without riding hyperscaler market shocks. They gain capacity they can count on and more time to build products that win.

We believe the market will not reward the largest models by default. It will reward clear economics, steady margins, and a clean path to profitability. Teams that optimize compute early will carry that advantage into every round that follows.

A Tougher Market, in Plain Terms

Cloud pricing is hard to navigate. Spot instances can be far cheaper than on-demand, but they come with eviction risk and scarcity. GPU demand has outpaced supply, and concentration in a single vendor creates exposure to shocks. Volatility from hyperscalers, influenced by tariffs and other political shifts, does not inspire confidence. Many AI startups spend a large share of capital on compute, and inference at scale can drive millions in monthly COGS before engineering and hosting. Meanwhile, senior engineering time is lost to orchestration instead of product.

The pattern is consistent. Costs rise, capacity fluctuates, focus drifts. The answer is not more brute force. It is smarter placement, better scheduling, and a reliable platform that treats compute like a portfolio to be actively managed.

What This Means for Customers

• Keep funding for growth, not GPU costs.
  
  

• Capacity you can count on, even when supply tightens.
  
  

• Less time on infrastructure, more time on product and customers.
  
  

• Swiss stability and reliability for mission-citical workloads.

Helio’s Proven Track Record

Helio reduces the operational effort of running fine-tuned models, trains where it makes sense, and places inference where cost and performance meet your targets. The Core makes multiple providers feel like one platform you can plan around. You submit work once, Helio finds the best place to run it, and you keep shipping.

When you remove volatility from the equation, companies, especially startups, protect liquidity. When you protect liquidity, you extend runway. That is the compounding effect we are building for our customers.

The People Behind It

Helio is led by builders who care about reliability and real-world results. Kevin Häfeli sets the vision to make computing power as accessible and abundant as sunlight. Tobias Bamert brings a customer lens to every decision. Michael Wiebel and Flavian Sierk focus on secure, scalable systems that simply work.

Looking Ahead

Our mission has not changed. From 3D visualization to AI, we match global compute capacity to demand. If you are building on AI and want more speed with more control, we would like to talk.