That can mean configuring pipelines, transforming and enriching data, removing duplicates, writing custom code, and testing whether everything behaves as expected. As products and pricing evolve, that work compounds. A new usage metric or pricing model can introduce another development cycle between the idea the business wants to bring to market and the infrastructure required to support it.
Zuora AI for Mediation helps shorten that path.
AI-assisted capabilities in Zuora Mediation help teams create meter logic, generate transformation code, and validate pipelines as they build, making it easier to move from a usage requirement to working metering logic.
Start with the usage model
Think about an AI company that’s introducing consumption-based pricing.
Its product generates millions of usage events across tokens, API calls, model interactions, or credits. Those events may need to be enriched with additional data, deduplicated, transformed, or aggregated before they become the units customers ultimately see on a bill.
The desired outcome might be simple: process incoming usage, remove duplicate events, apply the appropriate business rules, and send the resulting records downstream. Building that process is where complexity starts.
With AI-assisted meter creation, teams can describe the outcome they need and use that as the starting point for a draft meter. From there, they can review the proposed pipeline, refine its logic, and test how it handles their usage data.
For transformations that require custom logic, Zuora AI can generate JavaScript or Python for mediation operators. Developers get a starting point they can review and adapt rather than writing every transformation from scratch.
Meter validation brings that development cycle together by helping teams evaluate a meter as they design the pipeline.
The result is a more direct path between how the business wants to monetize usage and how that usage is actually processed.
Keep pace with evolving products and pricing
Getting a meter into production is only the beginning. Products change, pricing evolves, and companies learn more about how customers actually consume what they’ve built.
AI products are accelerating that shift. Monetization can involve tokens, API activity, actions, credits, prepaid balances, commitments, drawdowns, or combinations of several models. What works at launch may need to evolve quickly as consumption patterns and customer expectations become clearer.
The metering layer has to keep pace.
AI-assisted development makes it easier to create and modify the logic behind these models without turning every change into a ground-up development exercise. Teams can iterate on meters, generate custom transformations where needed, and validate changes before moving them forward.
That creates more room to experiment with how products are packaged and monetized without allowing implementation complexity to become the limiting factor.
And the opportunity extends beyond development.
Through Zuora MCP, mediation capabilities can also be made available to conversational AI experiences. Teams can inspect meters, validate configurations, and access information across connections, Event Stores, schemas, and meter audits, creating a more direct way to understand what’s happening within usage processing.
Over time, these capabilities lay the groundwork for an operational experience that can help teams investigate failed runs, understand where records changed or dropped, explain unexpected usage volumes, and determine where to look next.
A shorter path from product usage to revenue
Usage-based and AI business models are creating enormous flexibility in how companies monetize their products. They’re also introducing more complexity behind the scenes.
Mediation sits at the center of that challenge, transforming high-volume product activity into structured usage that can flow into billing and revenue.
Applying AI across how meters are built, tested, and operated can reduce the technical overhead required to support increasingly sophisticated monetization models. Instead of spending as much time translating business requirements into implementation, teams can focus on the decisions that differentiate their business: what to measure, how to package it, and how customers should pay for it.
Because ultimately, the goal isn’t simply to build a meter faster. It’s to move faster from how customers use a product to how the business monetizes that value.
Ready to simplify how you build and manage usage meters? Explore the latest AI capabilities in Zuora Mediation and see how your team can move from usage requirements to monetization faster.
[Learn more about Zuora Mediation →]
