The Progress® Corticon® platform helps organizations streamline eligibility determinations and claims adjudication by automating complex business rules, without sacrificing transparency or oversight. When policies evolve and decisions need to be defensible, the Corticon rules engine makes it easier to manage, adapt and trust your logic.
Organizations managing eligibility and claims processes face increasing pressure to deliver fast, accurate decisions while keeping up with constantly changing regulations and benefit policies. Relying on manual workflows or code-based rules can slow down response times, introduce inconsistencies and make it difficult to explain how a decision was reached, especially in high-stakes environments.
The Corticon decision automation platform separates business rules from application code, allowing rules to be authored, updated and deployed independently. This enables teams to automate decision logic at scale and across real-time and batch environments, while maintaining full visibility into how decisions are made.
Business users can manage logic using visual modeling tools, without writing code
Built-in validation highlights logic gaps, conflicts and redundancies
Versioning and audit trails support regulatory reviews and internal accountability
Integration with claims and eligibility systems through Representational State Transfer (REST) or Java APIs
Supports deployment in the cloud, on-premises or hybrid environments
Makes decisions clear and understandable with logic that’s easy to explain to auditors, reviewers and internal teams.
Quickly incorporates new regulations, benefit rules or reimbursement policies by modifying rules without re-coding applications.
Applies logic uniformly across teams and systems to reduce variance and improve reliability in decision-making.
Automates repetitive, rule-based decisions to reduce manual effort and frees up staff for higher-value tasks.
Empowers stakeholders with decisions they can trace and understand, building trust in your systems and processes.