We're investing €300K in AI

Why now

We've been integrating AI into our delivery workflow since mid-2025. It changed how we write code, test it, and ship it. But adoption across the team is uneven. Not everyone has had the opportunity to build fluency with these tools, and we want to change that.

We also want to be well versed in what happens under the hood — how retrieval pipelines, pre-processing, and fine-tuning shape the outputs we rely on. That understanding is what separates teams that use AI from teams that can build with it.

This investment tackles both: team-wide adoption of AI tooling, and the technical depth to build and train our own models.

Every role, not just engineering

AI tooling isn't only for developers. We want product owners, QA engineers, and designers working with AI daily — not as an experiment, but as part of how we deliver.

We call the target agentic engineering: AI handles repetitive tasks under human oversight, people focus on decisions and quality. Getting there requires training, practice, and time.

Understanding what's under the hood

We've worked with generative AI and computer vision across multiple projects — consuming pre-trained models through third-party services. They work well for many problems, but we want to understand why they work and what to do when they don't.

This investment funds dedicated time to build that knowledge:

• Fine-tuning foundational models for specific domains
• RAG (retrieval-augmented generation) — how retrieval and context shape model responses
• Training small models for narrow, well-defined tasks
• Computer vision — object and behaviour recognition from images and video

The goal isn't to replace third-party services. It's to know enough to make better decisions about when to use them, when to customise them, and when to build from scratch.

A project worth building

We want to use computer vision to recognise sign language and translate it into text or speech in real time. Solutions like this exist in research, but they're not widely available yet. We want to help change that. It sits at the intersection of computer vision, AI, and our belief that software should have purpose.

What we expect from this

• Our engineers keep pace with the shift. AI is redefining how software gets built. This is one of the most significant changes our industry has seen. We want our team equipped to lead through it, not react to it.
• We build real authority in AI. Fine-tuning models, building vision systems, designing domain-specific agents — we want to be subject matter experts in these areas, not just consumers of someone else's tooling.

If any of this resonates with what you're working on, or if you want to explore how AI can fit into your delivery, let's talk.