Revenue leakage detection for SaaS, services and telecom. We read your signed contracts, compare them line by line with what billing actually charged, and hand finance a ranked list of money owed, with the clause and invoice attached.
Revenue leakage detection is the continuous reconciliation of what customers agreed to pay against what you actually invoiced and collected. AI reads contract terms such as price escalators, usage tiers, minimum commitments and discount expiry dates, then compares them with billing and usage records. It outputs a prioritised list of under-billed amounts, each linked to the contract clause, the invoice and the usage data behind it.
Sales negotiates custom terms. Legal files the PDF. Billing is set up once, by hand, from an email. Nobody re-reads the contract at renewal, so escalators, overages and expired discounts drift for years.
Average value lost to inefficient contract management in revenue and cost efficiency, and up to 15%, per World Commerce & Contracting's 2025 research.[1]
Contract data is spread across 24 systems on average so no single team sees terms, usage and invoices together (WorldCC, 2025).[1]
of contract value is forfeited through mismanagement according to the 2025 WorldCC and Icertis Smarter Contracts, Better Margins report.[2]
Missed uplifts compound because each year's un-escalated price becomes the base for the next renewal.
Pulls commercial terms out of MSAs, order forms, amendments and side letters, and keeps the latest amendment in force.
Calculates what each invoice should have been from the terms and usage, then compares with what was billed.
Findings are scored by value and confidence, with a draft correction or credit note ready for approval.
We agree the metric, usually verified under-billing found, and pick a segment such as top 200 customers or one product line.
Commercial terms are extracted and a sample checked by your deal desk or finance lead against the signed PDFs.
Expected charges are rebuilt from terms and usage for the last 12 to 24 months and compared with invoices.
We walk finance through each finding with evidence. You decide which to bill, which to waive, and whether to go to Run.
| Criterion | Manual audit | Off-the-shelf tool | Stratgik build + run |
|---|---|---|---|
| Coverage | Sample of contracts, once a year | Contracts already in the vendor's CLM or billing | Every active contract, monthly |
| Non-standard terms and side letters | Found if the auditor reads them | Often outside the data model | Extracted and cited |
| Usage data | Spreadsheet exports | Native billing usage only | Product logs, CDRs, timesheets joined in |
| Evidence for customer conversations | Auditor notes | System record | Clause, invoice and usage pack per finding |
| Best fit | Low contract count, simple pricing | Standard pricing on one billing platform | Negotiated terms across several systems |
Independent research on contracting and telecom revenue assurance points the same way: companies lose real value between the signed terms and the invoice, and recover only part of what they find.
Enter your revenue and how much of it runs on negotiated terms. The leakage rate is an assumption; the pilot replaces it with a measured figure from your own book.
Illustrative estimate using your inputs and stated assumptions, not a quote or guarantee. The pilot measures the real figure against your baseline.
21-day pilot on up to 300 contracts and 24 months of billing
per month, monthly reconciliation of the full book
per month, multiple entities, products and usage feeds
Usage (model tokens, document processing, cloud hosting) billed at cost; data stays in your cloud account where required; no success fee; taxes excluded. GBP and AED prices are indicative conversions from USD.
Revenue leakage in SaaS usually comes from the gap between negotiated contracts and billing setup. Common causes are annual price escalators not applied at renewal, usage or seats above the committed tier billed at the base rate, promotional discounts that never expire in the billing system, and amendments that sales agreed but billing never saw. Each is small per invoice and large across a customer base.
AI revenue leakage detection works in three steps. First, it extracts commercial terms from contracts and amendments. Second, it rebuilds what each invoice should have been using those terms plus usage or provisioning data. Third, it compares expected with actual billing and ranks the differences by value and confidence, attaching the clause, invoice and usage records so finance can verify each one.
Our revenue leakage detection pilot is a fixed 15,000 USD for 21 days, covering up to 300 contracts and 24 months of billing. Ongoing monthly reconciliation runs from about 4,000 USD a month. There is no percentage of recovered revenue, so the cost does not grow with what we find. Model and cloud usage is billed at cost.
Often, but that is a commercial and legal decision, not a system one. Contracts vary on whether past under-billing can be invoiced, and many companies choose to correct pricing going forward or raise it at renewal instead. We give you the clause, the amount by period and the evidence; your finance, legal and account teams decide the approach per customer.
Yes. For telecom and usage-based models we reconcile rated usage such as call detail records, data sessions, API calls or metered units against tariffs and customer-specific rate cards. That covers unbilled usage, wrong rate plans, missed minimum commitments and partner settlement differences. High-volume feeds are processed in your data warehouse, such as Snowflake, BigQuery or Databricks.
We typically connect to Salesforce or HubSpot for opportunities and order forms, a contract repository such as Ironclad, DocuSign CLM, SharePoint or Google Drive, and billing in NetSuite, Zuora, Chargebee, Stripe, Maxio or SAP. Usage comes from product databases, metering tools or telecom mediation systems. Read-only access is enough for the pilot.
A 30-minute scoping call, then a fixed-price 21-day pilot with every finding backed by its clause and invoice.