Revenue Trust Layer Book audit

Revenue trust. Metric clarity. Safe automation.

Revenue Trust Layer

We make your revenue and customer data AI-ready by reconciling Stripe, CRM, accounting, and BI metrics before you automate workflows or launch copilots.

Get the 10-day audit Run quick diagnostic
10 days
to isolate metric trust gaps
4 systems
Stripe, CRM, accounting, BI
1 ladder
audit, fix, automate, monitor

The commercial problem

AI fails quietly when business data is already disputed.

Growing companies want AI agents, self-serve analytics, and automated reporting. The blocker is usually more basic: MRR, churn, active customers, refunds, disputes, and pipeline numbers do not mean the same thing across systems.

The fix is sequential: clean the data, define the metrics, automate the workflow, then monitor the AI.

01 Revenue reconciliation

Payments, refunds, failed charges, disputes, and accounting variance.

02 Metric definitions

MRR, ARR, churn, active customers, CAC, LTV, and retention logic.

03 Workflow reliability

Owners, retries, logs, alerts, handoffs, and exception handling.

04 AI readiness

Use cases ranked by data quality, risk, observability, and control.

Built around the tools growing teams already use
Stripe HubSpot QuickBooks Power BI Fabric dbt n8n Snowflake BigQuery

What we do

Three services. Each one earns the next.

Start with the audit. If the findings justify it, we build the fix. Then we keep it running.

First offer 10 days

Revenue Trust Audit

Find where Stripe, CRM, accounting, and BI disagree. You leave with a metric dictionary, source map, issue register, and a roadmap to fix what we found.

  • Revenue and customer data quality review
  • AI-safe use case assessment
  • Executive-ready findings report
Core build 2-4 weeks

Revenue Trust Dashboard

Build the trusted layer for MRR, churn, active customers, refunds, cancellations, and discrepancy alerts.

  • Power BI/Fabric or warehouse-backed model
  • Reconciliation logic and exception queues
  • Board and operator dashboard views
Automation 2-3 weeks

Reliable Workflow Sprint

Turn the reporting, CRM, and finance tasks your team repeats every week into monitored automations with logs, retries, and clear owners.

  • n8n, Make, Python, and API workflows
  • Failure handling and escalation paths
  • Runbooks for internal operators

Operating model

The sequence that keeps AI from amplifying bad data.

1

Diagnose

Map systems, definitions, dashboard logic, and workflow failure points.

2

Fix

Reconcile revenue, define metrics, and create trusted source rules.

3

Automate

Ship reliable workflows with logging, retries, and clear owners.

4

Monitor

Track discrepancies, stale data, broken workflows, and AI handoffs.

5

Assist

Add self-serve analytics and copilots only after trust exists.

Quick diagnostic

What's your Revenue Trust Score?

Six questions across the same dimensions we audit. Not a replacement for the full assessment, but enough to show where your revenue data stands.

Revenue Trust Score
50 /100
Significant Gaps
System Alignment
Metric Integrity
Data Hygiene
Payment Reconciliation
Reporting Reliability
Automation Readiness

Comprehensive audit recommended before expanding automation or AI.

Pricing

Start small. Expand when it makes sense.

Revenue Trust Audit

From $3,000 USD

Fixed scope. 10 days. For founder-led teams and RevOps.

Book audit

Trust Layer Build

From $12,000 USD

Dashboard, reconciliation logic, metric dictionary, and alerting.

Scope build

Monitoring Retainer

From $2,000/mo USD

We watch for metric drift, workflow failures, and new discrepancies so you don't have to.

Discuss retainer

Final price depends on how many systems are involved and how complex the setup is. We work with international clients.

What you get

Documents your team will actually use, not a slide deck.

Metric dictionaryWhat each metric means, who owns it, how it's calculated.
Source-of-truth mapWhich system is the authority for each entity and number.
Issue registerEvery trust gap we found, ranked by severity and effort to fix.
Reconciliation viewSide-by-side variance checks across Stripe, CRM, accounting, and BI.
Automation runbookHow each workflow runs, what to do when it fails, and who to call.
Revenue Trust ScoreYour 0–100 score across six dimensions, with grade and breakdown.

Who's behind this

I've sat inside these data problems and built the systems to fix them.

4+ years reconciling financial metrics at Allianz ($1.25B in capital instruments), building the retention and LTV/CAC dashboards at Origin Protocol ($150m in product launches), and designing financial infrastructure at Smith + Crown ($100m capital raise).

I also build the tools. Data quality engines that flag rule failures across financial operations. AI-assisted cleaning agents that profile and execute deterministic fixes. Decision-support systems for churn risk and retention. Production warehouses with dbt, Airflow, and SQL pipelines feeding dashboards that operators actually trust.

Revenue Trust Layer exists because I kept building these systems from scratch for every engagement. The audit, the reconciliation logic, the metric dictionary, the monitoring layer. It's always the same work. Now it's a service.

Allianz Consulting Origin Protocol Smith + Crown MSc Finance, Jönköping SQL + dbt + Power BI + Python
Etiosa Richmore on LinkedIn →

Buying questions

Common questions before booking.

Do we need a warehouse already?

No. The audit can start from exports, Stripe, HubSpot, QuickBooks/Xero, spreadsheets, and BI access.

Is this an AI agent build?

Not first. We get the data, definitions, and workflows right so AI can be added safely later.

Who should sponsor this?

Founders, CFOs, RevOps leads, or whoever is responsible for making sure the numbers are right.

What tools do you work with?

Power BI, Fabric, dbt, Python, n8n, HubSpot, Stripe, QuickBooks, Snowflake, BigQuery, and simple alerting stacks.

Get started

Book a 10-day Revenue Trust Audit.

Tell us what tools you're running, what's not matching, and what prompted you to look into it. We'll get back to you within one business day.

We'll follow up by email within one business day.