Service · AI Implementation
AI implementation for real business processes.
Implementing AI is not installing a tool: it is taking a selected use case to a pilot, integrating it into the way you work and measuring the result. We stay with you from decision to production — we do not stop at recommendations.
How it works
From use case to production, with decision criteria at every step.
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01 / 07
Process analysis
We understand the real process: who does what, with what information and where it hurts.
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02 / 07
Opportunity selection
We pick the use case with the best value-to-feasibility ratio.
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03 / 07
Business case
Cost, impact and evidence before investing: the pilot is born with decision criteria.
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04 / 07
Pilot
We build or test the solution in a real workflow, within weeks.
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05 / 07
Integration
We connect it to your current systems and constraints, without rebuilding your operation.
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06 / 07
Adoption
We train the team and adjust the solution to how they actually work.
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07 / 07
Measurement
Time, cost, errors, capacity: data to decide whether to scale, adjust or stop.
What you get
From strategy to production, with no orphaned pilots.
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A pilot with a path to production
Every pilot is designed to support a business decision, not to demo a technology.
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Integration and adoption
A solution connected to your systems and a team trained to use it with judgment.
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Measured results
Metrics agreed from day one and tracking of the actual improvement.
Case · Arbegui
From 2 hours to minutes per permit.
AI automation of special transport permit processing, integrated into the real process and adopted by the team.
See the cases →Frequently asked questions
How long does an implementation take?
The pilot produces measurable results in weeks; integration and adoption depend on scope, but they are planned from day one.
Pilot or proof of concept?
A PoC validates that something works technically; a pilot tests it in your real workflow with decision criteria. We prefer pilots: the technology is usually already proven.
Do you work with our current systems?
Yes. We start from your systems and constraints; we only recommend changes when the evidence justifies them.
What if the pilot does not work?
That is also a good outcome: you will have avoided scaling a mistake. The metrics tell you whether to scale, adjust or stop, and the learning stays with you.