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Plexify
Language: en

You bring AI into your organisation.
We bring organisation into your AI.

From process analysis to sovereign AI operations, advised independently and built to the EU AI Act.

Problem

Does any of this sound familiar?

  • Structure

    Who does what?

    Separate workflows, no standards, no documentation: the knowledge sits with one or two people, and new data silos grow unnoticed.

  • Data

    What do you need?

    The use case is clear, the data sits in three systems. But without a clean data position, every prototype stays a demo.

  • Spend

    What does AI cost?

    The bill climbs every month and nobody knows why. Three teams, one model, a single number on the credit card.

  • Compliance

    Who answers?

    The EU AI Act applies. But which risk class, which system, which decision: no log gives an answer.

Our stance

Your data. Your infrastructure. Your decision.

EU inference is the default. Where a frontier model is needed, we make the trade-off transparent, with zero data retention. Where on-premise AI makes sense, we run the numbers on hardware and operations, honestly.

  • Zero Data Retention
  • EU inference
  • EU AI Act compliant

Our solution

Four stages, one principle. Measure first, then decide.

  1. 01

    Readiness Check

    Full inventory, EU AI Act risk classification, potential map and roadmap across all departments.

  2. 02

    Analysis & baseline

    Measuring time, cost and quality per process. Improvements proposed against that baseline.

  3. 03

    Prototype with kill criteria

    Real processes, real data. Our evaluation framework compares models on efficiency, speed, cost and accuracy.

  4. 04

    Implementation & operations

    Production systems with cost tracking, tracing and audit trails. Dashboards included, handover to your team.

AI-native champion

Training and playbooks stay with you. We support you with updates, model re-evaluations, compliance audits and process checks.

Compliance

The EU AI Act is not a hurdle.

Documentation, logging and oversight are part of the architecture from day one.

Pseudonymisation before the model, role-based filtering before the output, need-to-know enforced by the system rather than wished for by policy.

What comes out of that is a system you can trust and can account for to an auditor at any time.

Experience

Our insights

  • From the assessments

    What the bill does not say

    Your model invoice knows tokens and models. It knows nothing about workflows, teams or outcomes. Which is why it cannot answer the one question the board asks.

  • From practice

    The first meter hung on our own AI

    Tokenometrics did not come out of a workshop. It exists because we could not explain our own invoice, and then found the same gap at every client we looked at.

  • More articles

AI was never a hype for us. It is our craft.

Contact

Ready for numbers instead of gut feeling?

Start with an assessment: fixed price, clear outcome, no obligation.
An answer within 24 hours.

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