AI Development

AI for problems software couldn’t solve before.

Agentic systems, AI grounded in your data, and complex data workflows. Built by senior engineers who have been bringing AI into real products since 2022.

Illustration: dog and monkey running toward X and O symbols

You’re in the right place if:

  • you want to know whether AI can genuinely improve your product. Or just make it more expensive.
  • you’ve already tried building with AI, but it never made it into reliable production.
Who we are2x10

At 2x10, you talk directly to the founders and the senior engineers who build your software. No account managers, no layers of juniors in between. We’ve been bringing AI into real products since 2022. Our own systems have served millions of users.

01

AI where it works

Not every problem needs AI. Sometimes a simple script is the better solution. We choose the technology that solves the problem, not the one that happens to be trending.

02

The right model, in the right place

Frontier models from Anthropic, OpenAI and Google when they fit. Open-source when control or local hosting matters. For sensitive workloads, data can stay in Austria. We pick the setup that fits.

03

Reliable under real conditions

LLM demos can look impressive very quickly. Production systems need to behave reliably under real conditions. That’s why we evaluate, test, monitor and measure instead of trusting the demo.

What you get

What that means in practice

Working systems

AI that can do more than generate text: research, plan and execute workflows.

01 · Base

Data foundation

Preparing, connecting and securing your data. The less visible work that often determines whether an AI product succeeds.

02

Proof in answers

Where the use case requires it, answers can be grounded in sources you can trace and verify.

03

Costs upfront

We account for model, infrastructure and operating costs from the start, so production economics don’t become an afterthought.

04 · Goal
Our takeStraight talk

AI projects rarely fail because of the model. They fail in execution.

The usual suspects:

  • Missing business value. “We’ll throw AI at it and see what happens” isn’t a product strategy.
  • Missing domain knowledge. The advantage comes from combining AI with your data, processes and know-how. Without that, it’s just another wrapper around an off-the-shelf model.

The question isn’t “Is the AI smart enough?” It’s “Does AI really add value here, and can your product do something an off-the-shelf model can’t?”

That’s where we start: your knowledge, your data and your processes. Then we work out where AI can create something an off-the-shelf model can’t.

01since 2022AI in real products
02Evals before releasetested, not assumed
03Open sourcefine-tuned, hosted in Austria
04Viennaseniors, direct line
“The companies in Austria that understand AI as well as 2x10 fit on a beer coaster.”
Head of IT · largest client · anonymous

A fit, if:

  • AI is central to your product
  • you have an ambitious AI product in mind
  • you bring your own data and knowledge
  • you want AI in production, not just a demo

Better elsewhere, if:

  • you just need a chatbot, that’s Blue Monkeys →
  • you’re looking for an AI workshop
  • you want AI mainly as a marketing label
  • you can’t provide data for AI to use

FAQ

Not always. If a simpler solution solves the problem, we’ll say so. We use AI where it adds real value.

It depends on the scope and complexity. Production-ready AI is a substantial investment. Smaller projects with us usually start around EUR 30,000.

Often the model isn’t the problem. The issue is usually the use case, data, integration or the path to production. We’ll look at what went wrong and tell you whether a second attempt is worth it.

We design the architecture around the sensitivity of your data and your requirements. Where needed, open-source models can run on infrastructure in Austria so sensitive data doesn’t have to leave the country.

Usually not from scratch. We work with proven foundation and open-source models, then use the approach the problem requires: for example retrieval, tool use, fine-tuning or local deployment. The value comes from how the model works with your data, systems and domain knowledge.

N° 06 Contact

Tell me what you’re planning.

No form, no ticket system. Email me directly and you get me, not an inbox someone else manages.

Moritz MiedlerMoritz Miedler · Founder, replies personally
2x10 Technologies · Viennahello@2x10.com