Automation & AI
Artificial intelligence for business
We add AI to business processes when it does a measurable job: reading documents, classifying requests, searching internal documentation, drafting replies. We integrate it with your systems, test it with your data and decide up front what happens when it gets something wrong.
Start a projectWhat automating with AI means
It's combining language or vision models with conventional software to handle tasks a fixed rule can't: unstructured text, documents in different formats, open questions. The model is one component in a system that also includes validation, permissions, logs and human review.
Documents or messages come in
In whatever format.
AI reads and extracts
With a confidence level for each value.
Rules that validate
Totals add up, the customer exists.
A person reviews anything uncertainPerson
And their corrections improve the system.
AI systems we build
Document extraction
Invoices, delivery notes, contracts and forms turned into structured data, with a confidence score.
Classification and routing
Emails, tickets and requests sorted and sent to the right queue or person.
Search across your knowledge
Answers based on your documents, manuals and records, citing the source.
Internal assistants
Tools that let your team ask about procedures, policies or data in plain language.
Drafting
First drafts of replies, reports or descriptions for a person to review.
Decision support
Recommendations with their reasoning shown; the final decision stays with a person.
Where AI helps and where it doesn't
- The input is unstructured: text, documents, images, conversations
- The volume makes handling it by hand expensive
- Occasional mistakes can be caught by validation or review
- There are real examples to test with
- A clear rule would give the same result more cheaply
- Not a single mistake is acceptable and nothing can be reviewed
- Someone wants to use AI without a specific task to solve
How we build AI systems
Define the task
One specific job, with an input, an output and a clear definition of what a correct result is.
Prepare a test set
Real examples from your data to measure accuracy before and after every change.
Prototype and measure
We compare approaches and models on your examples, including a non-AI option.
Integrate with safeguards
Validation, confidence thresholds, human review and logs inside your workflow.
Monitor
Accuracy and cost tracked in production; re-measured when models or data change.
Models, data and compliance
We're not tied to any provider: we choose the model for each task by accuracy, cost, speed and where the data can live. GDPR and the EU AI Act are taken into account from the design stage.
- Models
- Language model APIsOpen modelsOCR and visionEmbeddings
- Engineering
- Retrieval-augmented generation (RAG)Structured outputsTest setsPrompt versioning
- Control
- EU-hosted dataAccess controlAudit logsHuman review
To get started
Pilot project
from €250 + VAT
Together we pick one repetitive task in your company and build a first solution to automate it. If you like it, we move on to another.
- Process analysis
- Development
- Go-live
- Initial support
Frequently asked questions
Can AI be added to our current software?
Usually yes. AI features are normally built as a service your systems call, or as a step in an automated flow, so there's no need to replace what already works.
Is our data used to train models?
We don't do it, and we configure providers so they don't either. If data must stay in the EU or on your own servers, we choose providers or open models that allow it.
How accurate will it be?
We measure it before promising anything. It's tested on a set of your real examples, and the system is designed so a person checks uncertain results before they reach your records.
Related free tools
What's holding you back?
A process, a product idea, a device, a set of systems that should talk to each other. A few lines are enough to get started.
Tell us