We close the gap between the data you have and the decisions it should be improving. A small senior team that sits in your stack for a while, gets the numbers agreeing and builds the systems and AI that act on them.
Fast dashboards from templates. Breaks the moment your business doesn't fit the template.
Headcount that closes tickets. No one owns whether the numbers are actually right.
The right answer at scale. But it's four skill sets, not one, and each senior hire is slow, expensive, and a single point of failure.
Applied AI
Trustworthy AI analytics comes from a governed layer of your business definitions, not a smarter chatbot. We build it on the stack you already own, you keep every asset, and we stay accountable for accuracy as your business changes.
No new platform | No lock-in | Your definitions, in your repo
Answer accuracy, same AI model, before and after a governed definition layer
Anthropic internal results, 2026
In practice
Monday, 9:04am, in Slack
The driver breakdown, from governed definitions, before the coffee's done. No ticket, no analyst queue.
Mid board meeting
Answered live, and it matches the dashboard, because both read from the same definitions.
New hire, day one
The answer is in code, versioned and tested. Not in a veteran's head or a stale wiki page.
Before committing the promo budget
A forecast with the assumptions visible, so the debate is about the plan, not the numbers.
Health & Fitness SaaS
Found no reliable growth equation and metrics nobody trusted.
One trusted core metric layer: the growth equation, defined and tested.
Marketing, product, and ops reporting, added as the work earned it
Now including governed AI self-serve, live in production.
amp grew from under $1M to $30M ARR in that year. Data maturity stayed ahead of the business the whole way, so the right bets got pressed early and wrong turns got caught before they got expensive.
