AI runs on foundations. We build them.

We build the platform, data and business context that make AI work, then hand your team the keys.

Getting real value from AI happens in three stages. Skip one and the next one stalls.

Most companies are further along in some areas than others, so we start by finding out where you actually are.

Platform

A home for your data, and everything you'll build on it.

The problem

Data is scattered across business systems and spreadsheets, processes run by hand, and there's nowhere approved to run new apps or AI.

What done looks like

One governed place where your data lands, processes run on their own, and new apps can be deployed and shared safely.

What we do · 5

Set up your cloud foundation on GCP, Azure or AWS, with a warehouse or lakehouse in BigQuery, Fabric or Databricks
Build and orchestrate pipelines from your core systems
Put access, privacy and security controls in place
Write it all as infrastructure as code, so it's repeatable and reviewable
Prepare it to host what comes next: apps, agents and AI workloads with proper permissions

Data

Numbers everyone agrees on.

The problem

Every team calculates KPIs its own way, dashboards multiply, and leadership still can't get a straight answer about last quarter.

What done looks like

Certified metrics, models that run reliably, and a team that ships changes safely and quickly.

What we do · 5

Map your business domains and build metric trees that show which numbers drive profitability
Map every key metric and dashboard back to its source data
Build reliable, orchestrated data models in dbt (or your tool of choice)
Add data quality checks and a catalog with definitions and lineage
Improve how your team delivers, with Slim CI, automated testing and infrastructure as code for your data models: higher quality and a faster pace once we're done

AI

AI that knows your business.

The problem

You've rolled out Copilot, ChatGPT or Claude. People use it to write emails. None of it touches your data or your decisions.

Rolling out an AI assistant is the starting line, not the finish line.

Real AI enablement means AI working on your data, inside your workflows.

What done looks like

AI recommending and acting on your own data, inside real workflows, with governance in place.

What we do · 5

Map how your business makes money and where AI would have the most impact
Build the context layer (glossary, domains, definitions and data quality signals) so AI pulls the right data and understands your terms
Let business users create their own apps and reports ("dashboards 2.0") by describing what they need, while the platform handles infrastructure, data access and permissions
Build AI agents and MCP servers for specific workflows, using skills that draw on your data
Move from "automate this rule" to "given the data, what do you recommend?"

Across every stage

Every engagement includes enablement. We train your team on what we build so they can run and extend it after we leave.

Not sure where to start? Find out in five minutes.

Answer a few plain-language questions about your platform, data and AI. You'll see where you stand right away, and we'll send a full report with recommended next steps.

Start the self-assessment

Strategy draws the map. Squads do the work.

Strategy

Stuck? Start with a map.

If you don't know where to start, we'll find out together. Our maturity assessment shows where you stand across platform, data and AI, business unit by business unit, and turns that into a prioritized plan. Deliver it with us or with someone else. Either way, you'll know what to fix first.

The self-assessment is the free first step. The full assessment is the paid one.

See where you are

Squads

Senior squads, amplified by AI.

When you know where you're going, our squads get you there. Every squad is senior, and every squad works with the AI skills we've built and refined across years of delivery. You get the output of a much larger team from a smaller, more experienced one.

Software squad

Product manager / business analyst
Front-end engineer
Back-end engineer (often with DevOps)

Data squad

Product manager / business analyst
Lead analyst
Analytics engineer
Data engineer (often with DevOps)

The AI app layer Coming soon

Apps, reports and agents, built on your data foundation.

We're building a shortcut to apps, reports and agents created with AI, running inside your own platform and drawing on one shared context layer. Once your foundations are in place, this is how the business starts building on them.

Join the waitlist

Fixed price when it matters most.

Messy problem? We'll fix the price. Our teams are senior enough to know what they're walking into.

Project

A defined outcome at a fixed price.

Best for assessments, platform builds and data foundations.

Complex work is phased: a firm price for the first phase, then firm estimates as we learn.

Retainer

A senior squad on a monthly basis.

Best for ongoing data and AI work where the backlog keeps growing.

You choose the model. We make sure you're never locked in.

Have a team?

We train them.

Building a team?

We help you hire.

Need us to run it?

We do that too.

Ready to make your data and AI investment pay off?

See where you are Book a Discovery Call