Informat BPM and Workflow Automation FAQ: Process Design, Intelligent Orchestration, and Continuous Optimization in 2026
Business process management and workflow automation capabilities are core to the Informat platform, enabling organizations to design, automate, execute, monitor, and continuously improve business processes that span departments, systems, and human and AI participants. This FAQ addresses the most common questions about BPM and workflow automation on Informat in 2026.
How Do I Design and Automate a Business Process on Informat?
Informat provides a visual BPMN 2.0-compliant process designer where users model processes through drag-and-drop — defining tasks, decision gateways, parallel branches, timers, and escalation paths. The AI-augmented design capabilities accelerate process creation: the AI assistant can generate an initial process model from a natural language description ("design an employee onboarding process that coordinates HR document collection, IT account provisioning, facilities access setup, and manager introduction"), which the user then refines. Process models can incorporate human tasks (assigned to specific roles or individuals), automated tasks (executed by the platform), AI agent tasks (handled by autonomous agents), integration tasks (API calls, database operations), and business rule evaluations. Once designed, the process is deployed with one click — the platform handles the workflow engine execution, task routing, deadline monitoring, and escalation management. For guidance on effective process design, see our analysis of business process management and the shift to BPM 3.0.
How Does Informat Handle Process Exceptions and Edge Cases?
Exception handling — managing the cases that do not follow the standard process path — is where AI-augmented BPM delivers its greatest value over traditional workflow automation. Informat provides: boundary events that define what happens when something goes wrong — a task times out, an approval is rejected, an integration fails; AI-powered exception resolution where AI agents assess exception context, determine the appropriate response (retry, escalate, route to alternative path, request human intervention), and execute — handling the 80% of exceptions that follow known patterns without human intervention; intelligent escalation where exceptions that cannot be automatically resolved are routed to the appropriate human with complete context — what happened, what has been tried, what the AI recommends, and what the human needs to decide; and process instance monitoring and intervention where process owners have real-time visibility into every running process instance and can intervene — reassigning tasks, modifying due dates, skipping or adding steps — when business circumstances require process adaptation.
How Does Informat Support Continuous Process Improvement?
Continuous process improvement is enabled through the platform's process intelligence capabilities: process mining automatically reconstructs actual process execution from system logs — revealing the real paths work takes, including variants, bottlenecks, rework loops, and compliance deviations that process documentation misses; performance analytics provide metrics on process duration, wait times, task completion rates, SLA compliance, and resource utilization — identifying the specific process steps where improvement will have the greatest impact; AI-generated improvement recommendations analyze process execution data to identify optimization opportunities and simulate the impact of proposed changes — enabling data-driven process improvement decisions; and A/B process testing enables organizations to test process changes on a subset of instances and compare outcomes before rolling changes out universally — applying the experimental rigor of digital product development to process improvement. For a broader examination of process intelligence, see our analysis of process mining and AI-powered business optimization.