DATA & AI STRATEGY
We help data teams adopt AI tools that cut the grunt work, raise the quality of what they ship, and free business users from waiting in the queue.
Your data team is good. AI makes them better and faster
This is what you can expect for us to focus on.
AI powered development. How AI can help you in writing code and documentation, reviewing pull requests, automation of deployment processes and even write and restructure semantic models in your BI tools. Should I use Github CoPilot, Claude, Microsoft Copilot and what is the best setup?
Automate bug fixing in your data pipelines. Let AI analyse the issue, write code to fix the problems and draft pull requests such that your data pipelines remain reliable and downtime is minimized.
Let end users answer their own questions. Set up an MCP and AI Agents to help end users answer their own questions like “Where to find this data?” “What is the definition of this specific metric?” , “Why is performance in this area lower than last month?” This frees up a lot of time for your analysts they can spend on the more meaningful tasks.
Generic productivity improvements. <tbd>
WHAT YOU WALK AWAY WITH
Configured, working AI setup
Tools installed and integrated in your actual environment. Not a demo, but a live setup your team uses from day one.
Team trained and confident
Your engineers and analysts know how to use the tools in their daily work and when to reach for AI and when not to.
Backlog of next improvements
A prioritised list of further AI integrations your team can tackle independently, so momentum doesn't stop when we do.
THE CHALLENGE
Most data teams spend more time maintaining than building
Writing boilerplate SQL, updating YAML configs, chasing missing test coverage, answering ad-hoc questions that never quite make it into a dashboard. The list of low-value work is long. And it crowds out the high-value work your team is actually good at.
AI tools can take a significant chunk of that load off. But knowing which tools to adopt, how to integrate them into your existing stack and processes, that's where most teams get stuck. The AI tooling landscape moves fast. What didn't exist six months ago is now production-ready. We track it so you don't have to, and make sure your team adopts what's actually worth using right now.
WHAT THIS LOOKS LIKE IN PRACTICE
Want to see what AI can do for your data team?
We'll start with a no-nonsense conversation about your stack and where the biggest gains are.