Skip to main content

AI systems

AI strategy, data and AI agents

We get your data and processes ready for AI, then build the AI tools that run on them, inside the systems you already use.

Book a call See what we build

What we build

Strategy & Data

We get your data and processes ready for AI.

  1. AI Roadmap

    AI ideas everywhere, no clear priorities

    A concrete plan. Where to start and why

  2. Data Integration

    Same data, different numbers in every report

    One trusted source of truth, ready for AI

  3. Knowledge base

    Know-how in people's heads and old files

    Company knowledge AI can answer from

AI Product Development

We build AI tools that work inside your systems.

  1. Agentic Workflows

    Routine work done manually

    Agents run it for you in your systems

  2. AI Governance

    Every AI tool reaching your data its own way

    One access layer with rules and policies

  3. AI Data Pipelines

    Complex data that must be interpreted

    Millions of records turned into signals

Case studies

Measured in production

Assistant on a technical catalogue

users in the first 10 weeks
252
questions in the first 10 weeks
5,873
Read the case

One set of KPIs, rebuilt from the ERP

KPIs reconciled to the cent
21
source tables read every night
30
Read the case

Social posts turned into weekly trend signals

posts collected from 4 platforms
17.9M+
artists tracked
103,676
Read the case

How a project runs

The evaluation is how we show that a system works. The same four steps run on every project, with tools adapted to the problem.

  1. Step 1

    Agree what good means

    We agree with you, before we build, which answers count as right and how often they must be right.

  2. Step 2

    Build the test set from real cases

    Questions, documents and records taken from your own work.

  3. Step 3

    Measure every change against a baseline

    Each change is compared with the version before it, so a regression shows before release.

  4. Step 4

    Release on the result

    A change ships only when it meets the bar.

Common questions

What does AI data readiness mean?

It means the data an AI will use is consistent and trusted, because if two systems disagree, no AI can tell which one is right. For a wholesale distributor on SAP Business One we rebuilt 21 KPIs from the raw ERP tables and reconciled each one to the cent before any AI used them.

What can AI agents do for a business?

They can run routine work inside the company's own systems, once they have clean data, integration, rules and human verification. An assistant we built finds the right product in a large technical catalogue with sources, price, stock and lead time; 252 people used it in its first 10 weeks.

What is AI governance?

AI governance is the set of rules that decides what each AI tool may see and do. We build one access layer with rules and policies, so every AI tool reaches the data the same way. Our catalogue assistant reads the ERP as the signed-in user, and our KPI connector can only read.

Do you work with our existing ERP?

Yes. We connect to the ERP you run, including SAP, NetSuite, Dynamics 365 Business Central and Odoo, and choose the approach from your workflows and constraints.

How is custom work priced?

We price each project after scoping it with you. A phase with a clear scope and an agreed definition of "working" can have a fixed price. Production cloud costs sit on your own cloud bill.

What happens after a system is delivered?

The team that built it can keep it running, with a monthly package of support hours for questions, fixes, small changes, dependency updates and monitoring.

Ready to put AI to work in your systems?

Book a call and tell us which process you want to fix and where its data lives today.

Book a call