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.
Sound familiar
Underneath all four it is the same work, in the same order: make the numbers trustworthy, build the systems and agents that act on them, and hand it over working.
Proof
Different businesses, same approach. The full studies say how each result was measured.
The changes were earlier TV and direct mail flighting and a re-ranked channel mix. We will not claim the split between the measurement and a good year, and the team now runs the Monday numbers and the biweekly model without us.
One promo calendar for everyone became a per-customer decision about which offer or nudge comes next. What it optimizes toward is the same number finance reports, which is what made it safe to switch on.
Census, billing, and the CRM never agreed, and a person absorbed the difference by hand. The agent matches them overnight, clears routine mismatches on rules the operator signed off, and escalates only the genuine ones. Actions taken without approval: zero, by design.
Who does the work
There is no layer beneath us you have not met, and no account manager between you and the person building the thing. When scope grows we add senior people, and you meet them before they start.
Between us the team has run data programmes in pharma, banking, media, utilities, and identity alongside the consumer work: multi-billion-dollar initiatives, petabyte-scale infrastructure, and CISSP-credentialled security and governance. Which mostly matters because it means the governance, access, and security questions get answered on the first call rather than the third.
Most of our work comes through referrals, so the first conversation can just be about your problem. From there, engagements grow in small steps that each have to earn the next, and this is what that has looked like:
Health & Fitness SaaS
Cost nothing, took under an hour of their time, and found no reliable growth equation and metrics nobody trusted.
One trusted core metric layer: the growth equation, defined, tested, and agreed with finance.
Marketing, product, and ops reporting, each added when the last piece proved out.
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.
