Multi-Integration Automated Incident Management System (MIIMS)
Project description
The core design challenge of this project is how to automatically and reliably transform unstructured incident messages from multiple communication channels (Slack, email, and WhatsApp) into structured, actionable incident reports without placing additional burden on customers or responders.
This project explores the design of an extensible incident management system that integrates multiple messaging platforms, classifies incident severity (Minor, Major, Critical) using message analysis, and assigns someone to work on the incident manually and automatically through rule-based logic and round-robin scheduling. The solution will help to reduce response delays, eliminate subjective severity selection, and minimize dependency on individual team members, while remaining flexible for future integrations and operational scaling.
Context
The organization creates software systems that are critical to business operations and customer experience, making timely and consistent incident handling essential.
Incidents are currently reported through everyday communication channels such as Slack, email, phone calls, and WhatsApp, reflecting real-world customer behavior: because users expect to report problems quickly and informally, without navigating complex ticketing systems or forms. However, traditional incident management tools often require manual input, structured forms, or subjective severity selection, which can lead to misclassification, delays, and inconsistent responses.
Within this context, the project addresses the operational challenge of coordinating incident response across distributed teams, where availability, workload, and clarity of responsibility are crucial. The project also reflects modern software engineering practices, emphasizing API-driven integrations and containerized backend services. It is designed as a proof of concept that mirrors real production environments and can be extended to integrate additional monitoring tools and communication platforms in the future.
Results
The most important outcomes of this project are (1) a working automated incident intake system and (2) reliable two-way communication between clients and developers across platforms. The prototype demonstrates that incident reports can be submitted through familiar channels such as Slack, email, and WhatsApp, automatically captured, structured, and enriched with system-assigned severity levels, removing the need for manual triage.
Validation with realistic incident scenarios shows that this automation improves consistency and lowers the operational burden on both customers and developers. Equally important, the system enables two-way communication regardless of the original platform, allowing developers to respond, request clarification, and coordinate resolution without switching tools. This increases transparency and speeds up incident handling. Together, these outcomes position the project at TRL 4–5, as core functionalities are validated in a relevant, multi-channel environment.