revenueguard

The problem

Billing errors, expired discounts, and unbilled usage often go unnoticed in manual spreadsheets, leading to significant revenue leakage. Finance teams lack a privacy-first way to audit contract-to-cash cycles without uploading sensitive financial data to the cloud.

What it does

• Identifies missing recurring fees by comparing approved billing rules against actual invoice lines.
• Flags expired discounts and unit rate discrepancies between contracts and usage exports.
• Detects unbilled work by reconciling timesheets or usage records against billed quantities.
• Calculates minimum commitment shortfalls and flags cross-currency mismatches.
• Generates human-readable revenue assurance reports and structured review queues.

Frameworks & tools

Python 3. Requires local files in CSV, JSON, or XLSX format.

Why this beats prompting it yourself

General LLM prompting fails at financial accuracy and complex reconciliation across disparate datasets. RevenueGuard enforces strict decimal arithmetic, handles multi-file joins with evidence-backed findings, and ensures sensitive data stays on your local machine.

Use cases

• Auditing an agency's monthly billable hours against invoice records.
• Verifying SaaS usage records against monthly minimum commitments.
• Identifying customers still receiving discounts after promotional periods ended.
• Preparing periodic revenue leakage health checks for clients.

Known limitations

Supports monthly billing rules only. Dates must align with full calendar months. Requires structured data inputs and manual approval for all findings. Cross-currency arithmetic is blocked.