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The client is a leading provider of communication and security solutions for critical infrastructure and field-based assets. Their flagship platform integrates with advanced technologies such as CCTV, fiber-based intrusion detection, public address systems, and general alarms to deliver automated threat prediction and resolution. Focused on enhancing operational security and situational awareness, the client sought to modernize their platform with a rule engine that empowers both technical and non-technical users to build, test, and deploy custom workflows in real-time.
The client wanted to make their existing software solution more user-friendly and accessible for non-technical users. They wanted to create a Rule Engine Workspace that could be utilized by their clients to create rules using drag-and-drop operations. The client needed Codvo.ai to help them develop the Rule Engine Workspace and integrate it with their existing solution.
They also aimed to incorporate dynamic rule validation and real-time testing features to enhance usability and ensure accuracy before deployment.
Codvo.ai focused on developing multiple design engine automated workflows connected to external IoT devices. We started off with reviewing the execution flow and delivering a POC by integrating the test system for MQTT events. We also worked on delivering CDC (Change Data Capture)enabled events from Postgres with NATS Jetstream as Pub-Sub. Our team proceeded to formulate deployment instructions for Ubuntu based system for deploying microservices. We also worked on understanding whether Camunda would be our final choice for the rule engine and then doubled down on it. We validated the cause-and-effect test cases in Camunda.
We connected Debezium, Cassandra and NATS connector for CDC and build the initial database to store the workflow meta information. Once complete we set up Camunda on client infrastructure and the Camunda cluster for testing and designing the database workflow manager. We then set up the Postgres CDC to NATS in Linux VM and set up a test system to complete performance testing.
BPMN and DMN standards were used to model business processes and decisions within a process. Camunda Modeler was utilized for the development of BPMN and DMN visual modelers, and it was deployed on-prem. We managed the complete decision lifecycle from design to implementation to execution on the platform.
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-Codvo.ai enabled clients to develop a Rule Engine Workspace, allowing non-technical users to easily create rules through drag-and-drop for inputs, outputs, and functions.
-The workspace acted as a canvas for creating rules as a graphical flowchart, which made it easier for users to create and test rules.
-The dynamic rule validation and rule testing capabilities helped in improving the speed and accuracy of decision-making.
-The Automation Rule Engine provided a universal platform for users to define workflows on the web in open BPMN 2.0 standards, which made the solution more versatile and flexible.
-We ran a Reliability Test Result which showed that the solution was scalable, with a 40K+ workflows being run in 16 hours.
