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Corticon

Automate business processes with a business rules engine designed for the most rigorous business and regulatory requirements.

Progress Corticon Decision Management

Progress Corticon helps organizations automate complex, explainable business decisions while managing policy logic separately from application code.

Domain experts can author, test, and maintain sophisticated business rules using visual modeling tools, while development teams can deploy Decision Services across centralized servers, cloud platforms, serverless architectures, browsers, mobile applications, data platforms, and edge environments.

Both Corticon and Corticon.js are designed to execute sophisticated, mission-critical business rules and support enterprise production workloads. Corticon.js combines that decisioning capability with a portable JavaScript runtime that can execute centrally, in cloud and serverless services, or directly within web, mobile, data, and edge applications.

This site provides sample rule projects, integrations, workshops, and demonstrations for Corticon and Corticon.js.


Getting Started

  1. Learn the authoring environment

  2. Choose a sample or workshop from the repositories below.

  3. Import or open the project in the applicable Corticon development environment.

  4. Build, test, and deploy the Decision Service using the runtime and integration model appropriate for your application.

  5. Integrate the deployed decision logic through supported service interfaces, embedded runtimes, JavaScript function calls, or cloud-native application interfaces.


Enterprise Decisioning with Corticon

Corticon and Corticon.js share the same core objective: enabling organizations to externalize, automate, test, explain, and maintain sophisticated business rules independently from application code.

Both runtimes support enterprise Decision Services and high-volume decision workloads. The appropriate runtime depends primarily on the target architecture, integration requirements, operational model, and preferred deployment technology, not on whether the decision qualifies as an enterprise use case.

Corticon.js is not limited to user-interface logic or small edge applications. It supports centralized Decision Services, high-volume transaction processing, eligibility and benefits determination, compliance, financial services, insurance, public-sector casework, cloud-native applications, and other demanding decision workloads.

The choice of runtime is an architectural decision rather than a measure of the complexity, scale, production readiness, or business importance of the decisions being automated.


Deployment Models

Runtime Deployment options Key strengths Representative uses
Corticon Corticon Server, Web Console, embedded Java or .NET, on-premises infrastructure, virtual machines, containers, and cloud environments High-performance enterprise decisioning, centralized administration and monitoring, enterprise data integration, Java and .NET embedding, and scalable server-based execution Centralized Decision Services, high-volume transactional and batch processing, compliance, eligibility, underwriting, claims, and case management
Corticon.js Node.js services, containers, cloud services, serverless functions, browsers, mobile applications, embedded JavaScript environments, data platforms, and edge environments High-performance enterprise decisioning in a portable JavaScript runtime, flexible horizontal scaling, cloud-native deployment, low-latency embedded execution, and the ability to place decisions directly within applications and data platforms Centralized Decision Services, high-volume transactional processing, cloud-native APIs, eligibility, compliance, dynamic forms, embedded application decisions, serverless workloads, mobile applications, and edge execution

Featured Repositories

Samples for building and deploying Corticon.js Decision Services in JavaScript environments. The repository includes importable rule projects, extended operators, service callouts, asynchronous invocation examples, JavaScript framework integrations, browser applications, and cloud deployment patterns.

Importable sample rule projects for Corticon Studio. The examples demonstrate rule-modeling techniques across business, technical, mathematical, data-integration, and decision-automation scenarios.

A rules-driven, framework-independent approach to building dynamic forms with Corticon.js. Business rules control form navigation, field visibility, validation, and behavior separately from presentation code.

End-to-end demonstrations of executing Corticon.js Decision Services with MarkLogic. The repository includes examples for auto-insurance underwriting, Medicaid eligibility, and trade-data settlement.

Code samples demonstrating integration with and extension of Corticon Server, including Java-based extensions and a Python REST example.

Samples for capturing and persisting Corticon Server rule-execution information for auditing and analysis. Review the repository requirements and applicable Corticon version before using the examples.

Hands-on workshop materials that introduce Corticon through a Medicaid eligibility scenario. The learning path covers vocabulary design, Rulesheets, Ruleflows, Ruletests, explainable outputs, rule-modeling practices, and solution integration.


Additional Resources

An interactive knowledge resource for exploring Corticon concepts and related information.

Solutions to historical Corticon newsletter rule-modeling challenges.


Application Scenarios

Both Corticon and Corticon.js can support sophisticated, high-volume, and mission-critical decision automation. The deployment architecture determines where and how the Decision Service operates, not whether the underlying business decision qualifies as an enterprise use case.

Representative scenarios include:

  • Eligibility, benefits, and casework decisions for government and public-sector programs
  • Compliance and policy automation with transparent, explainable outcomes
  • Underwriting, claims, lending, and fraud-related decisions
  • Healthcare, insurance, and financial-services policy administration
  • High-volume transactional and batch decision processing
  • Centralized Decision Services exposed through APIs
  • Cloud-native and serverless Decision Services
  • Dynamic, rules-driven forms that adapt in real time
  • Decisions embedded within web, mobile, desktop, data, and edge applications
  • Offline decisions where network access is intermittent or unavailable

Choosing a Runtime

Both Corticon and Corticon.js support sophisticated enterprise Decision Services. Select the runtime based on where decisions need to execute, how they will be integrated and operated, and which deployment architecture best supports the application.

Consider Corticon when:

  • Decision Services will be deployed and centrally managed through Corticon Server and Web Console.
  • Java, .NET, or existing Corticon Server integration is required.
  • The organization uses Corticon Server administration, monitoring, and deployment practices.
  • The application requires Corticon Server extensions, server-managed data integration, or server-specific capabilities.
  • A managed server platform is preferred for transactional or batch decision processing.

Consider Corticon.js when:

  • JavaScript or Node.js is the preferred enterprise application runtime.
  • Decision Services will be deployed as centralized Node.js services, containerized APIs, cloud services, or serverless functions.
  • The architecture requires high-volume decision processing with flexible horizontal scaling across runtime instances.
  • Decision logic must execute close to the application, user, event, or governed data.
  • The same decision technology may be used across centralized services, browsers, mobile applications, embedded environments, data platforms, or edge environments.
  • Portable, self-contained JavaScript deployment is important.
  • Low-latency local or offline execution is part of the application architecture.
  • The surrounding platform will provide deployment, observability, scaling, and operational management.

These considerations describe different deployment and operational models. They do not establish a hierarchy of rule complexity, decision importance, production readiness, performance, or enterprise scalability between the runtimes.

A solution may also use both runtimes when different application components have different deployment, integration, or operational requirements.


Documentation and Support


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  1. corticon.js-samples corticon.js-samples Public

    Samples for using Corticon.js decision services.

    JavaScript 12

  2. corticon-classic-samples corticon-classic-samples Public

    Rule projects to import into classic (non-javascript) version of Corticon Studio

    TSQL

  3. server-analytics server-analytics Public

    Starting with Corticon v7.0, new analytics capabilities allow you to capture the details of rule execution; this enables auditing of individual decision service executions and analysis of decision …

    Java

  4. corticon-dynamic-forms corticon-dynamic-forms Public

    The Corticon.js Dynamic Forms Solution empowers you to create complex, multi-step web forms where the logic, flow, and validation are managed by business rules, not front-end code.

    JavaScript

  5. corticon-on-marklogic corticon-on-marklogic Public

    Demo repository of example for executing a Corticon.js decision service within a MarkLogic database

    JavaScript

Repositories

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