The brands with numbers they trust don't have better tools. They have a few people who know how to run them.
Anyone can ask a question in Claude, or whatever AI tool you use, and know whether the answer is safe to act on.
A plugin in your AI org that reads only governed metrics, says when something isn't defined yet, and is kept current as the business changes.
AI on your data →One net revenue, one new-customer count, one CAC.
Shopify, Klaviyo, Meta, Google and the warehouse reconciled in dbt, with the reasons they differ written down. Finance and growth plan on the same number.
Analytics & reporting →The repetitive ops work that doesn't need a hire.
Small in-house tools for the gap between what your systems do and what the team patches with spreadsheets: delivery exceptions, 3PL rebooking, address checks, conversation QA. Built to how you operate, inside your stack, and close to free to run once they exist.
AI systems & agents →Marketing measurement that doesn't depend on GA4 or a platform's pixel.
A tracking plan and a pixel on your own domain, so sessions reconcile to orders and attribution, geo tests and MMM read off data you own.
Growth marketing →Clear reporting on the same definitions the AI reads.
KPI-tree dashboards in whatever you already use, so a chart and a chat answer can't disagree. The weekly read comes with them.
Analytics & reporting →One question each, answered well enough to change a decision.
Is retention worsening by cohort, which promo paid for itself, where the funnel leaks by device, how long to run the test. Starts with a free audit of where you stand.
eCommerce growth →What each option costs a month, and what it costs you beyond the invoice.
Every answer says whether you can act on it.
Most teams already point a model at their data, and some of those answers are right. The problem is nobody can tell which, because the right ones had a rule layer underneath and the wrong ones didn't. We build the layer in your stack, every answer carries a flag, and you own all of it.
How the governed layer works →gross_bookings) by week vs the same week last year (364-day alignment), plus the promo calendar, via the dbt Semantic Layer. I can share the compiled SQL if you want to check it.Illustrative example.
What happened when we did it.
Different businesses, same approach. The full studies say how each result was measured.
Every platform reported a channel worth keeping. On the brand's own yardstick four were cut and Google non-brand was scaled despite its last-click ROAS. Post-purchase surveys agreed. We won't claim the split between the measurement and a good year.
amp chose Salesforce and NetSuite as it scaled; we built the integrations so one order flowed through all of them, and cancellations fell ~35%. Once Salesforce was mostly a ~$300k a year front end, we replaced it with a system amp owns, running for about $30 a month.
Category and audience data kept pointing at an adjacency the roadmap had no view on. The analysis put a defensible range on the opportunity, so the decision to enter was made on numbers rather than instinct.
We start by doing some of the work, because it is the fastest way for both of us to know if this is worth it.
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: a free look, a fixed first build at $3-5k, then $3-8k a month priced by scope. This is what that has looked like:
amp went from metrics nobody trusted to a growth equation the whole company could bet on.
Along the way, amp replaced its SaaS spend, mostly Salesforce, with a system on its own AWS and warehouse. It was built inside the embedded engagement with no separate build fee, tailored to how amp works, and connected to Intercom so support, orders and customer data sit in one place to act from.
Start where it hurts, or start with what needs building.
Every engagement starts with one gap in one place, not a transformation. Pick whichever door fits how you think about it.
Get in touch.
Tell us what you are trying to figure out. If we can help, we will say how. If we are not the right fit, we will say that too, and point you somewhere better.