Implement an AI-driven system that can analyze the granular task data and construct a holistic view of the business processes. This AI system can Collect and aggregate the vast amounts of user action data from the system. This includes every task data points, user clicks, form submissions, errors, and more. Use deep learning models to identify patterns and sequences in user actions. These patterns can be used to map out the flow of various business processes. As more data is collected, the AI system would continuously refine its understanding of the business processes. This ensures that any changes or evolutions in processes are captured in real-time. Present the constructed business processes in an intuitive dashboard. This allows stakeholders to understand the flow, bottlenecks, and efficiencies at a glance.

Extract the necessary data from the platform and preprocess it to ensure it’s in the right format for analysis. Utilizing machine learning, we created algorithms capable of identifying dependencies and relationships between tasks and incidents. Through the ML models, we generate estimates of how tasks are connected, identifying which tasks trigger or precede others. We render the identified relationships as intuitive and interactive dependency-graphs and decision-tree type graphs, allowing for clear visualization of the connections. The solution is seamlessly integrated the existing platform, ensuring a cohesive user experience. After thorough testing, we deployed the solution and continue to gather feedback for ongoing improvements.

By integrating a conversational AI into the application ecosystem, users can seamlessly seek guidance on tasks, ask questions, or fetch data. The AI, recognizing user struggles or errors, proactively offers assistance, ensuring a smoother and more efficient user experience.