AI Solutions
Large language models, document processing and intelligent assistants that bring measurable efficiency to your workflows.
AI as a business outcome, not a feature
Most AI projects start with an impressive demo and never reach production. The cause is rarely the technology; it is an unclear goal. Every AI engagement we run starts with one question: which process gets how much faster or cheaper? If the answer is not measurable, we don't start.
Use cases
- Internal knowledge assistants: answer questions from your documents and procedures with citations, respecting access rules (RAG)
- Document processing: extract structured data from invoices, delivery notes, contracts and forms and push it into your systems
- Support automation: classify, prioritise and route tickets and draft replies
- Content generation: product descriptions, report summaries and multilingual drafts
- Agentic workflows: multi-step automations that work across several systems with a human in the loop
How we make it reliable
Evaluation first
Before building, we assemble an evaluation set from real examples. Every change is measured against it — numbers, not gut feeling.
Humans stay in the loop
For high-stakes decisions the AI proposes and a person approves. When the system is unsure, it says so.
Data security and privacy
Masking personal data before it reaches a model, enterprise data processing agreements, access control and logging are part of the design.
Model-agnostic architecture
Model providers change fast. We build an abstraction layer so switching models for cost, speed or quality does not mean rewriting the application.
Connected to your systems
AI creates value by talking to your systems. We connect it to ERP, CRM and document archives through system integration and API development. Often the AI component is part of a larger custom software project.
Our Process
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Opportunity Analysis
Processes where AI creates measurable value are identified and ranked.
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Proof of Concept
A 2-4 week prototype with your real data, measured against an evaluation set.
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Production Hardening
Security, authorisation, monitoring and cost controls are added.
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Launch & Improve
Quality is continuously measured and improved with usage data and feedback.
Frequently Asked Questions
Will our data be used to train models?
No. We use enterprise API agreements under which submitted data is not used for training. Personal data can be masked before it is sent.
What if the AI gives a wrong answer?
We design systems that cite sources, flag uncertainty and require human approval for critical decisions. Quality is measured continuously.
Can we run a model on our own servers?
Yes. Where data must not leave your network, we can deploy open-weight models on your infrastructure.
How should we start an AI project?
With one well-defined, measurable process. A 2-4 week proof of concept lets you make the investment decision with real data.