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The demo worked. So why is it still a demo?

We take AI from pilot to production inside your product: the data and context layer that stops it making things up, the interface that makes it usable, and the cost that makes it viable. We are not selling you a model or a platform.

Tell us about your case

This sounds familiar if…

  • The assistant answers well in the demo and makes things up with real data.

  • Every system calls the same thing by a different name and the AI inherits the chaos.

  • The inference bill grows faster than the value it generates.

  • You put a chat on top of everything and users don't use it.

  • There are five AI pilots in the company and none has an owner, a metric or a path to production.

What we do

01

Diagnosis of the pilot. What task it solves, for whom, with what data, at what cost. If the answer is “we don't know”, that is where we start.

02

Semantic layer and canonical model. A common language over your systems so the AI works with reliable context instead of the quirks of each database.

03

The architecture your case needs. RAG, agents, fine-tuning, private inference: we choose by task and cost, not by trend.

04

Interface for AI. Chat is not the answer to everything. We design how the user sees, corrects and trusts what the AI proposes.

05

Production and operations. Evaluation, observability, guardrails and cost under control. What separates a pilot from a product.

We have done this before

Others: operations dashboards with generative AI (−38% critical errors), private-cloud AI inference for an operator (in progress).

What we don't do

We don't sell a model, a platform or hours of “AI consulting”. If your problem can be solved without AI, we will tell you; it will be cheaper.

Start with 30 minutes

Bring the pilot. We leave the session knowing what it needs in order to become a product.

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