Data & Analytics Advisory
We help growing companies build the data function they need next: the team, the infrastructure, the numbers everyone trusts. From the first data hire to ML in production.
Trusted by teams at
Who we help
Why teams call us
Your advisors have sat in the seat — owning the numbers, the roadmaps, and the models inside hyper-growth tech companies. You get judgment formed by doing the job, not observing it.
A recommendation doesn't fix a pipeline or ship a model. We define the KPIs, stand up the infrastructure, build the models, and hire the people who'll own them — alongside your team, not from the sidelines.
The goal isn't another consulting relationship. We build the team, the systems, and the decision-making so your company owns its data function — and scales it without us.
What we do
Three stages of one progression: people, then foundations, then business impact.
Build the team
We design the organization, define the hiring and sourcing strategy, and run the search ourselves — sourcing, screening, closing. Then we coach the leaders and teams once they're in the seat.
Build the foundation
We set up data infrastructure from scratch — or audit what you have and fix what's broken. We define the company KPIs everyone can stand behind, so every team plans and reports from the same truth.
Turn data into results
Pragmatic machine learning and analytics that move the P&L: churn prevention, pricing, cost reduction. Scoped, shipped, and measured against the outcomes they were built for.
Engagements rarely fit a template, and we take on very few at a time. If your problem touches data, talk to us — the list above is where most clients start, not where the work ends.
Selected work
12 weeks
From zero to a working data team.
0 → 20
A full data organization, built in one year.
90 days
From spotting a revenue opportunity to launching the product.
European creative marketplace
The company needed a data team, not a plan for one. We designed the hiring strategy, then ran it end-to-end: sourcing, screening, and helping close both the individual contributors and the Head of Data.
US health-tech unicorn
A year-long partnership: a reporting function became a full-stack data science organization, with company-wide KPIs and production ML to show for it.
US supply-chain startup
We embedded with the team and went looking for money the data was leaving on the table.
“They came back with an opinion about what we were doing wrong and what we were leaving on the table — and they didn't yield until we, as a team, listened. What we've built as a result is first of its kind.”
CEO, US supply-chain startup
About
Fifteen-plus years in data: building data teams at Uber through its hyper-growth years, leading data at startups as they became unicorns and kept scaling, and founding a profitable AI company along the way. Still hands-on — from SQL to org charts.
Next step
Bring your hardest data question — the numbers, the team, the infrastructure, the models. You'll leave the call with a clear read on your situation, whether or not we work together.
Two lines on where data hurts is plenty — we'll take it from there.