Patlytics analyzes patents with AI. They track thousands of patents, generate automated analysis reports, and bill customers based on what they actually use. Their pricing model mixes usage-based billing for API calls with seat-based billing for platform access, plus self-serve checkout for small customers and sales-led contracts for enterprise deals.

Before Measure, they were managing all of this across Stripe, HubSpot, and QuickBooks. Each system had its own version of the truth.

No single source of truth

Patlytics was running revenue operations across three disconnected systems: Stripe for self-serve billing, HubSpot for sales pipeline, and QuickBooks for accounting. Each system had its own version of customer data, subscription status, and revenue numbers.

When a customer upgraded mid-cycle, the sales team would update HubSpot, but Stripe wouldn't reflect the change until someone manually synced it. Usage data lived in their product database, but reconciling it against invoices meant exporting CSVs and running manual checks. Finance had to pull reports from three places just to close the books each month.

The bigger problem wasn't the manual work. It was that nobody trusted the numbers. Sales, finance, and customer success were all looking at different data and making decisions based on conflicting information.

Manual workflows everywhere

Sales reps had to manually create quotes in HubSpot, then re-enter the same pricing information into Stripe to generate invoices. If a customer wanted to add API usage credits mid-contract, that meant updating the subscription in Stripe, logging the change in HubSpot, and hoping accounting caught it during month-end reconciliation.

Limited flexibility also meant Patlytics couldn't easily test new pricing models. They wanted to offer prepaid credit packages alongside their subscription plans, but Stripe couldn't support that without custom engineering work. Enterprise customers needed annual contracts with quarterly invoicing and usage reconciliation, which required even more manual intervention.

The deployment

Paul Mooney, Patlytics' founder, came to the onboarding call with a Notion doc of his pricing structure. Measure's team went through it live: usage-based API billing, seat-based platform access, self-serve checkout, sales-led contracts, QuickBooks sync.

They configured everything during the call. By the time it ended, Patlytics had a working revenue system that unified self-serve and sales-led motions, tracked usage automatically, and synced directly to accounting.

What changed

Unified go-to-market operations

Self-serve customers hit Measure's hosted checkout and get provisioned automatically. Sales-led deals flow from HubSpot into contracts and subscriptions without manual data entry. Both motions feed the same revenue reporting dashboard, so everyone sees the same numbers.

Streamlined financial operations

Invoices generate automatically based on usage and subscription data. Payment collection, dunning, and retry logic all run through Measure. QuickBooks sync means finance isn't manually reconciling three systems every month. Their third-party accounting partner called it out: "This is awesome. I'm not doing manual anything for these guys."

Seamless API integration

Patlytics' engineering team integrated Measure's usage metering API for tracking patent analysis requests. Product usage flows directly into billing without CSV exports or manual reconciliation. The integration was straightforward enough that their engineers had it running in under a week.

Pricing experimentation ready

Since deploying Measure, Patlytics has tested multiple pricing variations without pulling engineering resources. They can configure new plans, adjust usage tiers, or modify contract terms through Measure's interface, then ship changes to customers the same day.

Conclusion

Patlytics went from three disconnected systems to one unified platform. Their sales, finance, and operations teams now work from the same source of truth. And when they want to test new pricing or launch new products, they don't need an engineering sprint to make it happen.

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