For Startups

Early-stage data work fails in two directions. Either nothing is built until the numbers are already untrustworthy, or a platform gets built for a company ten times the current size and consumes engineering capacity that should have gone to the product.

We aim at the middle: the smallest foundation that supports the decisions you need to make over the next eighteen months, built so it can be extended rather than replaced.

What this usually looks like

• Before the first data hire. Defining the role, sizing what it needs to cover, and building enough infrastructure that the person you hire is not starting from nothing.
• When reporting stops being trustworthy. Two dashboards disagree, nobody can say which is right, and the answer has become “ask an engineer.”
• Ahead of a raise or a board cycle. Metrics that are defined, reproducible, and defensible under questioning.
• When AI is on the roadmap. Usually the honest finding is that the data foundation needs work first — we would rather tell you that early.

How we work with early-stage teams

Managed services over bespoke infrastructure. A small team should not be operating something a large team built.

Explicit about what to defer. Most of the value in an early-stage roadmap is in what it tells you not to build yet.

Sized to actual constraints. Engagements are scoped to what a pre-Series-B budget can carry, and we will say plainly when the work does not justify an outside party at all.