Predict Process Outcomes
Know Where Every Process Is Heading
Predict the likely outcome of an in-progress process based on its current execution path and historical process behavior.
Flowra Lens evaluates the activities already completed, the path being followed, and relevant process patterns to identify cases that are likely to result in delays, exceptions, SLA breaches, rework, or unfavorable outcomes.
Identify At-Risk Processes Before They Fall Behind
Detect process instances showing early signs of delay or SLA failure.
Flowra Lens continuously analyzes execution behavior to identify cases likely to exceed expected processing times, helping teams prioritize high-risk work before deadlines are missed.
Anticipate Exceptions
Detect Problems Before They Become Exceptions
Historical process behavior can reveal patterns that precede failures and exceptions.
Flowra Lens uses AI to identify process conditions and execution patterns associated with future exceptions, enabling teams to intervene before a case follows a problematic path.
Forecast Process Workloads
Prepare for What Comes Next
Predict changes in process volumes, workload, and operational demand using historical execution patterns and current process behavior.
Understand where workloads are likely to increase and proactively align people, resources, and capacity to maintain process performance.
Plan ahead instead of reacting to demand
AI-Powered Risk Signals
Know Which Processes Need Attention Now
Flowra Lens continuously evaluates process execution to surface early indicators of performance degradation and emerging operational risk.
AI-powered risk signals help teams prioritize cases based on their likelihood and potential impact, directing attention to the processes that need intervention most.
Turn millions of process events into the signals that matter
Prescriptive Process Intelligence
Don't Just Predict the Problem. Know What to Do Next.
Prediction becomes more valuable when it leads to action.
Flowra Lens combines predictive intelligence with process context to help teams determine where intervention is needed and what actions can improve the expected outcome.
When a process is predicted to breach an SLA, enter an exception path, or experience a delay, Flowra Lens can surface the contributing factors and highlight potential improvement actions.
Process Prediction
Predictive Process Intelligence
Anticipate What Happens Next. Act Before It Happens
Move beyond understanding what happened and what is happening now. Flowra Lens uses AI and predictive analytics to understand where your processes are heading—anticipating delays, SLA breaches, exceptions, and adverse outcomes before they impact the business.
By continuously evaluating process execution, historical patterns, current activity, and contextual signals, Flowra Lens identifies cases that are likely to deviate from expected outcomes. Teams can intervene early, prioritize the right cases, and take corrective action while there is still time to change the outcome
Why?
Predict the Unpredictable
Anticipate emerging risks, delays, and exceptions before they affect process outcomes.
Know What Comes Next
Predict upcoming events, process paths, and likely outcomes using AI-powered process intelligence.
Intervene Before It Matters
Identify at-risk cases early and take action while there is still an opportunity to change the outcome.
Protect Process Integrity
Detect deviations, control gaps, and compliance risks as they emerge.
Drive Predictable Outcomes
Improve efficiency, reduce operational risk, and deliver more consistent business and customer outcomes.
How Process Prediction Fits into the Bigger Picture
Process Prediction works alongside four other capabilities to form a complete Process Intelligence framework — connecting foresight with the visibility, diagnosis, and validated improvement that surround it.
Process Discovery
Automatically reconstructs as-is process flows, primary paths, and variants directly from execution data, giving teams a clear picture of how work truly moves across people, systems, and applications.
Process Analysis
Compares actual process execution against expected behavior, policies, and SLAs to surface deviations, conformance gaps, and the root causes driving delays, rework, and exceptions.
Process Monitoring
Tracks process execution in real time, measuring current performance and the impact of changes so teams can see how processes behave as conditions evolve.
Process Simulation & Optimization
Tests what-if scenarios—automation, resourcing, routing, and sequence changes—against real process history before they go live, confirming expected impact on cost, cycle time, throughput, and compliance before committing to change.
Connect Regoxa to the Way Your Business Works
Connect Regoxa to Any Enterprise System
Regoxa is built to fit into your existing technology ecosystem—not force you to replace it. With support for SOAP, HTTP, event-driven architectures, microservices, and service-based integrations, Regoxa can seamlessly connect document intelligence, workflows, process intelligence, and AI capabilities with the systems your business already relies on.
From enterprise applications and legacy platforms to modern cloud-native architectures, Regoxa provides multiple integration options to embed intelligence wherever it is needed.
Integrate Your Way
API & HTTP Integration
Connect Regoxa with web applications, enterprise platforms, and external services using flexible HTTP-based APIs.
SOAP & Enterprise Services
Integrate with established enterprise and legacy systems through SOAP-based services without requiring major changes to existing infrastructure.
SOAP & Enterprise Services
Integrate with established enterprise and legacy systems through SOAP-based services without requiring major changes to existing infrastructure.
Event-Driven Integration
Respond to business events in real time. Trigger document processing, workflows, validations, or downstream actions as events occur across your enterprise.
Microservices Architecture
Deploy Regoxa capabilities as part of modern microservice ecosystems, enabling modular, scalable, and independently managed integrations.
Linux Service Deployment
Run Regoxa integration components as a service on virtually any Linux environment, making it suitable for on-premises, private-cloud, edge, and hybrid deployments.
Plug-and-Play Web Components
Accelerate application integration with ready-to-use jQuery-based plugins that allow Regoxa capabilities to be embedded directly into existing web applications with minimal development effort.
Flowra Lens evaluates the activities already completed in a case, the execution path being followed, and relevant historical process patterns to predict the likely outcome of an in-progress process. This allows teams to identify cases likely to result in delays, exceptions, SLA breaches, rework, or unfavorable outcomes well before the process concludes.
Flowra Lens uses AI to identify process conditions and execution patterns that have historically preceded failures or exceptions. By recognizing these early warning signals as a case progresses, it enables teams to intervene before the case actually follows a problematic or non-compliant path.
Process forecasting predicts changes in process volumes, workload, and operational demand using historical execution patterns combined with current process behavior. Flowra Lens uses this to help teams understand where workloads are likely to increase, so they can proactively align staffing, resources, and capacity ahead of demand instead of reacting to it after the fact.
Predictive process intelligence tells you what is likely to happen; prescriptive process intelligence tells you what to do about it. Flowra Lens combines predictive signals with process context so that when a case is predicted to breach an SLA, enter an exception path, or experience a delay, it can surface the contributing factors and highlight potential improvement actions—moving teams from insight to action.
Flowra Lens builds predictions from a combination of historical execution patterns, the current activity and path of an in-progress case, and relevant contextual signals. Continuously evaluating this data allows predictions to stay current as new process events occur, rather than relying only on static, backward-looking analysis.
Yes. Flowra Lens identifies cases likely to result in rework, delays, or unfavorable outcomes based on the execution path already taken and comparable historical cases. Because this is detected while the case is still in progress, teams can intervene early enough to change the trajectory of the case rather than only measuring the impact after it happens.
Flowra Lens pairs each prediction with process context, so predictions come with an explanation of contributing factors and suggested improvement actions—not just a risk score. This prescriptive layer helps teams move from "this case is likely to breach its SLA" to a clear next step, closing the gap between anticipating a problem and actually preventing it.
Predictive process analytics identifies deviations, control gaps, and compliance risks as they emerge—not after a process has already broken down. By continuously monitoring execution against expected patterns, Flowra Lens helps organizations detect risk early, protect process integrity, and reduce the operational and compliance exposure associated with undetected process failures.
Predictive workflow intelligence ranks in-progress cases by their likelihood of deviating from an expected outcome, so teams know where to focus first. Flowra Lens surfaces at-risk cases early—based on execution path, historical behavior, and contextual signals—allowing teams to prioritize high-impact interventions instead of reviewing cases at random or only after problems occur.
AI-powered risk signals are continuously generated indicators that surface emerging operational risk and performance degradation before they escalate. Flowra Lens evaluates process execution in real time and prioritizes cases based on the likelihood and potential impact of a negative outcome, helping teams focus attention on the processes that need intervention most—turning large volumes of process events into a manageable set of actionable signals.