Cleverbridge Uses Snowflake Cortex AI to Accelerate Insights Across $1B+ in Global Software Commerce

Selling software globally has never been as simple as opening a checkout page. Behind every international transaction are payment preferences, tax rules, compliance requirements, fraud controls, currencies, languages and customer expectations that vary by market.

For more than 20 years, Cleverbridge has helped software companies manage that complexity. As a premium global commerce platform and Merchant of Record running on Amazon Web Services (AWS), Cleverbridge handles payments, taxes, fraud prevention, compliance and other operational requirements so clients can sell in more than 240 markets with less risk and friction.

But managing complexity is only part of the value. Cleverbridge also helps clients see what’s happening across markets, understand where buying journeys break down, and decide where to act next.

That work depends on data. Analytics plays a central role in how Cleverbridge supports clients, giving teams greater visibility into commerce performance and the factors that influence conversion, renewals and revenue growth. Now, working closely with Snowflake as an early adopter of Cortex AI, Cleverbridge has taken its data analysis a step further, using Cortex AI agents to support fast natural language queries and reduce manual reporting work for engineers and customer-facing teams.

With its natural language analytics experience, Cleverbridge is making data easier to access, improving business decisions, and preparing for a future where AI plays a larger role in how software companies operate and grow.

In global software commerce, small performance improvements can create significant revenue impact. That’s why robust analytics have always been at the heart of Cleverbridge’s offering. The company supports more than $1 billion in software sales through its platform, helping clients understand performance, identify friction and improve returns over time.

“Everything we do involves optimizing very small percentages,” says Radu Immenroth, Chief Technology Officer at Cleverbridge. “There is a lot of complexity and countless possible combinations when you think about different countries, payment methods and trade laws. We need to be able to drill really deeply into that data.”

While the company provides performance insights to internal users and clients through business intelligence dashboards, sometimes users have more complex requests. Historically, those requests required engineers to develop SQL queries, which could be complicated and time-consuming. Cleverbridge turned to agentic AI to provide a simpler way to access insights at speed and scale.

“We wanted more people to access data more easily, through natural language. But we also knew there would be a huge advantage in seeing what people ask agents,” says Emanuela Premoli, Director of Product at Cleverbridge. “If we can understand what people want to know, we can create new products and dashboards to meet common needs.”

To provide access to data with minimal engineering effort, Cleverbridge set out to create a natural language analytics experience that could support monthly performance reviews, strategic business insights, forecasting and scenario analysis. The goal was to automate data exploration, segmentation and initial analysis, while allowing customer success managers (CSMs) to interpret the results and recommend the right next steps.

Cleverbridge originally planned to build these capabilities in-house. However, while proofs of concept worked, the project quickly became more complex as data volumes and business requirements grew.

“When we scaled our pilots, we were only getting around 60% accuracy,” says Immenroth. “When you’re working in a high-stakes environment, that lack of accuracy can have seven-figure repercussions.”

That experience clarified what Cleverbridge needed from a long-term AI foundation: enterprise-grade reliability, trusted data access and a roadmap that could support future agentic workflows. Snowflake stood out for its reputation, scale, secure data sharing capabilities and pace of innovation.

“We were quick to explore AI, and Snowflake is among the fastest-moving companies in this area,” says Immenroth. “It provided the reassurance, features and product roadmap we needed.”

Using Cortex AI, Cleverbridge was able to build its natural language analytics experience in just a couple of weeks, saving an estimated 13–21 months of engineering effort. In addition, the company estimates a potential long-term operational savings equivalent to three full-time employees annually.

With Snowflake CoWork, Cortex Search and Cortex Analyst, Cleverbridge’s data users can now explore structured and unstructured data using natural language prompts. In just a few months, the results have been significant.

The natural language analytics experience has enabled faster identification of performance drivers, helping teams connect KPI movements to root causes and reduce the time it takes to turn data signals into operational decisions and business strategy. As a result, Cleverbridge CSMs have saved over a thousand hours, representing a 33% reduction in the time it takes to pull insights together.

“It used to take hours to produce performance reports for clients,” says Premoli. “Now, it takes five or ten minutes for an agent to produce a slide deck. The reaction from users is really incredible, and we’ve saved the equivalent time of around one full-time CSM a year.”

With faster access to insights, Cleverbridge can provide more timely and relevant performance updates to clients. That speed matters because faster analysis can help identify issues and opportunities tied to conversion, renewal performance and average order value.

Agentic AI is already helping data teams access insights more quickly and share them more broadly. These capabilities also prepare companies for emerging changes in how people interact with software platforms.

“We need to think about how we position ourselves as a SaaS company in an agentic world,” says Immenroth. “In the future, people will use AI agents to remotely control SaaS systems like ours, so having those agentic capabilities at the heart of what we do represents an evolution for us as a software platform.”

As Cleverbridge continues to work with Snowflake, it plans to make the agentic experience available to clients as well as internal users. This will elevate the client experience by allowing users to drill into more detailed analytics on demand, while freeing Cleverbridge’s engineers to focus on more complex, bespoke queries that add further value.

Cleverbridge also intends to incorporate more unstructured data into its workflows, drawing on the expertise it’s gained over more than 20 years of helping software companies sell globally.

“There’s a huge amount of value in our experience,” says Immenroth. “We’ve generated so much knowledge since 2005, including millions of A/B tests, for example. Snowflake will help us unlock this and share it with our clients.”