Sparkling Logic Adds Transparency and Explainability in Latest Release

Sparkling Logic continues to drive innovation in simplifying decision management

Sunnyvale, CA, April 15, 2022Sparkling Logic today announced that it has released a new version of their SMARTS™ decision management platform to add more transparency and explainability in decision management.

Key enhancements in the latest release include the following:

  • New high-level expressions that make decision logic more compact and easier to understand, modify, and manage
  • Decision debugging enhancements that enable users to more easily identify errors and bottlenecks at a granular level
  • Augmented user interface to further simplify decision authoring, lifecycle, and administrative tasks

“SMARTS™ was created for business analysts and non-technical users to have more control over decision management,” said Carole-Ann Berlioz, Co-Founder and Chief Product Officer at Sparkling Logic. “With our latest release, we’ve made it even simpler for users to understand and explain the decisions that they’re managing throughout their lifecycle.”

In addition to making decisions and decision management more understandable, additional integrations have been added to offer organizations even more flexibility when connecting to external systems and services.

Additional Resources

About Sparkling Logic
Sparkling Logic Inc. is a Silicon Valley company dedicated to helping businesses automate and improve the quality of their operational decisions with a powerful digital decisioning platform, accessible to business users and “citizen developers”. Sparkling Logic’s customers include global leaders in financial services, insurance, healthcare, retail, utility, and IoT.

Sparkling Logic SMARTS™ (SMARTS for short) is a cloud-based, low-code, AI-powered business decision management platform that unifies authoring, testing, deployment, and maintenance of operational decisions. SMARTS combines the highly scalable Rete-NT inference engine, with predictive analytics and machine learning models, and low-code functionality to create intelligent decisioning systems.

See SMARTS™ in Action