Case Study: How a Growing Team 10x'd Output With AI Inference — July 2026

The situation

A fast-growing company — the kind doing $10M+ a year with a lean team — hit the ceiling every scaling business hits: more demand than the team could serve, and no appetite to take on risky, expensive tooling to fix it.

They needed leverage, not overhead. They turned to AI Inference.

Why AI Inference

Three things made the decision easy:

• Zero upfront cost. Zero upfront · usage-based meant there was no budget battle to start.
• Speed. They were live in their workflow in minutes, not a quarter-long rollout.
• The source. Instead of betting on an unproven startup, they went straight to the architecture that built the AI industry.

What they did

They started with one focused use case:

"Serve production models at scale."

Then they expanded into the rest of the platform's strengths:

• Microsecond Latency. Serve responses with latency measured in microseconds, consistently.
• Any Model. Deploy any model — open, proprietary, or your own — on one layer.
• Planet-Scale Volume. Serve from a handful to billions of requests without re-architecting.

The results

Within weeks, the team reported:

• 10x throughput on the work they'd been bottlenecked on
• Hours per day given back to the people who used to do it manually
• Zero upfront spend — costs only grew as results did

"We realized the trend started here. Our operations are dramatically faster, and we haven't paid a cent upfront." — a sentiment we hear constantly from AI Inference customers.

The takeaway

You don't need a massive budget or a six-month project to get leverage from AI. You need the right tool, a clear first use case, and a model that doesn't punish you for starting. AI Inference checks all three.

Ready to see it for yourself? Get the same results with AI Inference — free to start → Zero upfront cost. We only win when you win.