Technology

Model-agnostic by design.

We are not resellers for any model provider. We pick what fits the use case, and we can change it when something better arrives - without rebuilding your system.

0
vendor lock-in
100%
actions auditable
GDPR
compliant providers only
AI Act
ready

The right model for the job

A model that reasons well over long documents is not the one you want answering a phone call in 300 milliseconds. We benchmark against your data and pick per use case, so cost and latency stay where they need to be.

  • Benchmarks run on your own data
  • Per-use-case selection, not one model everywhere
  • Swappable providers without an architecture rewrite
  • Cost and latency tracked per operation

Data protection

Your data is not used to train third-party models - that is a contractual condition, not a preference. Where policy requires it, systems run on infrastructure you control.

  • GDPR compliant models and providers only
  • No third-party training on your data
  • European or self-hosted deployment available
  • Full audit trail of every agent action

AI Act ready

The EU AI Act applies across the Union, with obligations phasing in through 2026 and 2028. We classify each system, document what the regulation requires, and keep that documentation current as it evolves.

  • Risk classification for each deployed system
  • Technical documentation as required
  • Human oversight designed in, not bolted on
  • Compliance maintained as deadlines arrive

How we choose and run models

The decisions that determine whether a deployment stays affordable and defensible over time.

Benchmarked on your data

Public benchmarks say little about your documents and your vocabulary. We measure candidate models against cases you have already handled.

Per use case, not per company

A model that reasons well over long contracts is not the one answering a call in 300 milliseconds. Choosing once for everything costs money or quality, usually both.

Providers are swappable

The architecture separates what your system does from which model runs it. A better or cheaper model can be adopted without rebuilding.

Cost tracked per operation

Not a monthly total you cannot decompose. You see what each automated action costs, which is what makes the ROI figure real.

Data stays yours

Contractually, not as a preference: your data is not used to train third-party models. Where policy requires, systems run on infrastructure you control.

Everything is logged

Every action, its inputs, its outcome. That is what makes an AI decision explainable to an auditor, a regulator or a customer.

Technical questions we get

Which models do you use?
Whichever fits the case: OpenAI, Anthropic, Google, Mistral or open source models we host. We are not a partner of any of them, which is deliberate - it keeps the choice honest.
Can it run on our infrastructure?
Yes. Where data residency or policy requires it, we deploy on infrastructure you control, including fully on-premise with open models. It costs more to run and we will tell you when it is not necessary.
What does AI Act readiness actually involve?
Classifying each deployed system by risk, producing the technical documentation the regulation requires, designing human oversight into the flow rather than adding it later, and keeping that current as obligations phase in through 2026 and 2028.
How do you handle model updates?
Providers deprecate and change models on their own schedule. Because the architecture separates system from model, a migration is a tested swap rather than a rebuild - and we regression-test against your own cases before switching.

Questions about architecture or compliance?

Bring your security or legal team to the call. Technical questions get technical answers.

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