ACTICO Decision Management Platform vs Drools

ACTICO Decision Management Platform automates operational decisions by combining data, rules, and machine-learning models. It is aimed at banks, insurers, and other regulated organizations handling mission-critical decisions. AI agents can build and adapt graphical decision models, while experts review and approve changes before deployment. Decisions, rules, and models are designed to remain transparent, traceable, and auditable. Machine-learning models from Python or other frameworks can be incorporated into decision logic, and Model Hub versions changes and records approvals. The execution engine is designed to run complex decisions in milliseconds. Pre-built integrations and connectors link external applications and data; Java-based custom connectors are also supported. Deployment options include ACTICO Cloud, a customer’s own cloud, or on-premise hosting, with private deployment on AWS, Azure, Google Cloud, and Kubernetes. ACTICO states certifications including ISO 9001, ISO 20000-1, ISO 22301, ISO 27001, and SOC 2. Starter on-premise costs €4,500 per year, prepaid, and includes one named Modeler user, one Model Hub instance, one Execution instance with two cores, and standard support. The platform lists Linux, macOS, self-hosted, and Windows availability.

Drools is a free, open-source rule engine for building expert systems with forward- and backward-chaining inference. Its DMN engine supports Conformance level 3, covering the features in that standard, and can statically analyze decision tables for gaps and overlaps. For event processing, it reasons over streams using temporal operators, sliding windows, and event expiration. Developers can define rules in DRL text files alongside Java code, or use Excel decision tables, rule templates, or a Java executable model API. Rule units organize rules with typed containers for input data, and Kogito can generate REST endpoints from them. Drools rules can also be called by a BPMN business rule task in jBPM within the same service. Apache KIE states that the DMN engine passes 99.9% of DMN TCK tests as of version 10.2.0. The project is available for API, Linux, and self-hosted use at free. Getting started requires an IDE, JDK 21 or 17, and Maven 3.9 or later. Apache KIE is undergoing incubation and has not yet been fully endorsed by the ASF.