How Separating Business Rules from Application Code Enabled Pramata to Boost Its Agility

How much money are you leaving on the table?

In a business world driven by razor-thin profit margins, this is the question that keeps executives up at night. And answering that question is only getting more complicated. With important customer data siloed across systems, it’s easy to miss potential revenue opportunities.

“It’s a nightmare for large enterprises,” explains Pedram Abrari, who is the Chief Technology Officer at Pramata. “Revenue leakage happens bit by bit, but it adds up fast.”

Pramata aims to solve this challenge by helping customers digitize their critical contracts. By converting commercial contracts into a strategic asset, businesses can uncover revenue opportunities within these contracts and improve customer satisfaction.

To bring this commercial relationship data platform (CRDP) to life, Pramata needed a better way to manage business rules. This would help them extract key pieces of information from these contracts and apply business logic to better surface potential opportunities.

Abrari is a thought leader in the field of business rules, so he knows the space better than most. The problem with many business rules engines, he noted, is that they are primarily built around the inference engine. They aren’t well suited for actually modeling complex rule sets and automating their deployment.

For Pramata, this approach wasn’t viable because about 30% of the rule set had to be customized to each client. Pramata needed a rules management system that enabled its business analysts to write, test and debug rules in a quick and efficient manner without relying on IT to implement them first.

Fortunately, Abrari had already solved that problem a decade earlier when he led the development of Progress® Corticon®. Now, he was returning to the business rules engine—but this time, as a customer.

With a unique Excel-like spreadsheet UI, Corticon makes it easy for business analysts to model vocabulary and rules. Corticon also supports testing, debugging and deployment of rules with advanced analysis tools for decision logic validation, providing interactive assistance to find and fix errors in the logic.

By separating the rule modeling from the application code, Pramata is able to accelerate the time it takes to customize its solution for each customer. Corticon offers transparency into the rule modeling and execution process, enabling the analysts to see how the platform is arriving at decisions and validate the results.

Coming at Corticon with a new perspective as a customer and end user, Abrari was immediately impressed by the improvements made to the BRMS since he stopped working on it. In fact, one data access feature that had been completely rearchitected wound up being instrumental in Pramata’s use case.

“I kept discovering more and more, and getting more and more impressed with what Corticon is capable of,” he said. “The ease of use, the complexity of the problems it could solve, everything."

“Corticon has taken some giant leaps forward, and I’m still amazed the rest of the market hasn’t even come close to touching Corticon,” he added.

Since incorporating Corticon as a part of the next- generation CRDP platform, customer feedback has also been great. Now, Pramata’s clients get answers immediately—they no longer have to analyze data or do any of the leg work to get the decision.

“Getting our business experts into the driver’s seat is key to the success of our platform,” said Justin Schweisberger, Chief Product Officer, Pramata. “The level of agility Corticon gives us has been critical in accelerating not only our product roadmap but also the time to value for our customers.”

About Pramata

Pramata delivers an innovative solution that helps some of the largest B2B enterprises maximize customer lifetime value by dramatically improving install base selling and helping account management teams achieve their account revenue plans.