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Billing Pipeline Integrity Sprint

Seven days, one boundary of your billing pipeline, and working code that shows exactly where your numbers disagree — and why.

For usage-based SaaS, AI infrastructure, cloud and infrastructure companies, and any business whose billing runs through several systems.

Every system works. The pipeline still gets it wrong.

A usage charge passes through several systems before it reaches your books. Each can do its own job correctly while the handoffs between them lose, repeat or misprice data. Typical causes:

  • Missing events
  • Duplicate events
  • Retries that are not idempotent
  • Late events landing in the wrong period
  • Usage attributed to the wrong customer
  • Aggregation errors
  • Pricing and rating errors
  • Credits applied incorrectly
  • Invoices that do not match rated usage
  • Differences between billing and the ERP
  1. Product and operational events

    Check: emitted once per action

  2. Usage and metering

    Check: aggregated per customer and period

  3. Pricing

    Check: rated at the contracted price

  4. Billing platform

    Check: credits and plans applied

  5. Invoice

    Check: lines equal rated usage

  6. ERP and finance

    Check: revenue matches invoices

A typical usage-based billing pipeline. The sprint takes one boundary between two of these.

The sprint

One important boundary. For example: usage events → billable usage → your billing platform, such as Stripe.

Read-only by default. We start from read-only access, exports, historical samples or anonymised identifiers. Write access to production is normally not needed.

The acceptance principle. Every item in the chosen sample either reconciles or appears as an explicit, explained exception. Nothing is left unaccounted for.

Starting engagement

$5,000, fixed scope

Seven days. One boundary. Output you keep.

  1. Day 1

    Choose the boundary

    Agree the one boundary that matters most and the sample to test — a period, a set of customers, a product line.

  2. Day 2

    Get the data

    Read-only access, exports or historical samples. Customer identifiers can be anonymised.

  3. Day 3

    Write the rules

    Define what 'correct' means at this boundary, as rules that can be checked.

  4. Day 4

    Build the harness

    Match both sides record by record and run the rules.

  5. Day 5

    Explain every exception

    Classify each difference and trace it to a cause.

  6. Day 6

    Harden

    Tests, re-runnable scripts, and a runbook.

  7. Day 7

    Hand over

    Walk through the findings and the code with your team.

What you receive

Working engineering output, committed to your repository — not a slide deck.
Reconciliation harness
Code that compares both sides of the boundary, record by record, and runs again whenever you need it.
Deterministic integrity rules
Each rule written down and encoded, so the same input always gives the same verdict.
Automated tests
Tests for the rules themselves, so the harness can be trusted and changed.
Missing and duplicate detection
Events absent on one side, or present more than once, identified by key.
Exception dataset
Every item that does not reconcile, with the rule it failed and the evidence.
Traceability
From any invoice line back to the events it was built from.
Reusable queries and scripts
Yours to keep and run inside your own environment.
Findings and runbook
What we found, what likely causes it, and how to run the harness after we leave.

Know which boundary worries you?

Tell us about the systems in your billing pipeline and where the numbers stop agreeing. We will tell you whether a sprint fits and what it would test.

Discuss a Billing Integrity Sprint