Estimated costs reported as fact
COGS, freight, and fees filled with assumptions but presented like measured truth.
Reconcile orders, COGS, fees, CAC, returns, and channel mix.
Explore Revenue Leak Map → 02Build one trusted foundation beneath reporting and decisions.
Build the data foundation → 03Identify the data, workflow, ownership, and governance blockers.
Run an AI Stack Audit → 04Turn manual operating workflows into reliable decision loops.
Automate the workflow →Revenue Leak Map reconciles order, cost, return, fee, and acquisition data so teams can see where reported growth is not becoming profit.
Explore the worked example →
Choose the regional calculator that matches your operating context and inspect every assumption behind the result.
Choose your calculator → Free sampleSee how findings, assumptions, evidence gaps, and next actions appear in a clearly labelled synthetic report.
Inspect a sample → Fixed scopeMap the data and system constraints behind a stalled AI initiative and leave with a practical readiness verdict.
Explore the audit →From messy source systems to trusted decisions and production AI without forcing a platform replacement.
Power BI · Looker · Tableau · OpenAI · Claude
dbt · Python · Airflow · Fivetran
BigQuery · Snowflake · Databricks · Postgres
Shopify · Salesforce · SAP / ERP · Stripe · HubSpot · GA4
Dashboards and AI can sound certain while the data underneath remains unresolved. We make the uncertainty visible, reconcile what can be proved, and state where the evidence still stops.
COGS, freight, and fees filled with assumptions but presented like measured truth.
Customers, orders, or entities duplicated across systems that never agreed.
The same metric reported three ways with no defensible source of truth.
What is happening. Why. What to do next. And where you should not trust the answer yet.
Where an offer has a fixed scope, the price is published on its page, with no form required. For build and retainer work, where the scope varies, we agree a fixed price in writing before any work begins, so you never get an open-ended bill. Tell us what you need and we will point you to the number that applies.
For most growing teams, a scoped engagement gets you further, faster, than a hire. We reconcile the systems behind your critical metrics, build the reliable pipelines, and hand them to your team to own, so you add senior data and AI capacity without a headcount decision or a long ramp. If you hire later, you inherit clean foundations instead of a backlog. See how this plays out in our case studies.
Most first engagements ship in one to two weeks, not months. We scope tightly on purpose, so you get a working result, whether that is a reconciled number, an automated workflow, or a 90-day roadmap, quickly enough to act on it this quarter.
Access is scoped to the engagement and nothing more, granted least-privilege and revoked when we finish. We work inside your existing warehouse and tools rather than copying data out, so your data stays under your control, and we are glad to work within your security review and sign a standard NDA and DPA.
We work best with two kinds of teams: founders from seed to Series B who want one automated workflow shipped fast, and data teams at growing companies getting ready for production AI. If your decisions ride on numbers you are not fully sure you can defend, that is exactly what we fix, and a short fit call is the fastest way to find out if we are right for you.
A short working conversation about the problem, the available data, and whether there is a credible next step.