Why Traditional RPA Monitoring Falls Short — and How Radium AI Solves It

As organizations accelerate their digital transformation through Robotic Process Automation (RPA), many are discovering a major oversight: traditional monitoring and support tools were not designed for a world filled with hundreds of autonomous digital workers.

The Problem with Traditional RPA Monitoring

1. Siloed, Platform-Specific Views

Legacy RPA tools offer platform-bound dashboards that lack the unified visibility needed for enterprise-wide monitoring. This fragmentation creates blind spots and delays.

2. Manual Resolution Workflows

Traditional setups depend on human effort to triage errors, route tickets, and resolve issues—leading to slow response times and high support overhead.

3. Lack of Proactive Intelligence

Conventional tools only alert after a bot failure occurs. There’s no intelligence to detect trends, classify root causes, or automate incident handling.

4. Missed Optimization Opportunities

Without holistic insights into bot runtimes, license utilization, and failure patterns, businesses can’t maximize their automation ROI.

How Radium AI Transforms RPA Monitoring and Support

Radium AI was built to reimagine digital worker management—not just as a product, but as a vision for self-governed automation ecosystems.

🔍 Real-Time Incident Classification

At the heart of Radium is a powerful ML engine that analyzes bot failures and instantly answers:

• Who should resolve this issue?
• What action should be taken?

By automatically assigning the right resolver group and recommending targeted actions, Radium significantly cuts down response times and support effort.

⚙️ Automated Issue Resolution

Radium goes beyond suggestions. Its in-built action library can take corrective measures autonomously, enabling seamless recovery from known errors.

With Radium’s low-code workflow engine, you can:

• Define custom auto-actions to respond to specific bot failures
• Connect to multiple data sources via pre-built nodes
• Resolve even complex L2 issues without writing code

Core Features at a Glance

📊 Execution Report

Detailed views into bot performance, including run statuses and average run times—giving operations teams precise control over digital workforce health.

🧠 Platform Report

Interactive heatmaps and deep insights into license utilization and agent workloads—so you can better optimize resources.

📈 Incident Report

Trend-focused incident analytics help teams identify recurring problem areas and plan mitigation strategies—essential for long-term RPA scalability.

🔄 Aggregation Across RPA Platforms

Radium integrates with UiPath, Automation Anywhere, and Blue Prism—aggregating execution data into one centralized repository for smarter classification and analytics.

🧾 Integrated Ticketing via ITSM Systems

Radium AI works with tools like ServiceNow to auto-generate and route tickets, removing the need for around-the-clock human monitoring.

The Radium AI Philosophy: Support That Scales

“Your RPA initiative doesn’t end with bot deployment.”

Without intelligent post-deployment support, digital workers become liabilities instead of assets. Radium enables enterprises to scale automation confidently, with always-on support, actionable insights, and auto-remediation built-in.

Final Thoughts

Radium AI solves the long-standing gaps in RPA monitoring by delivering:

• Unified visibility across platforms
• AI-driven classification and response
• Auto-remediation via low-code workflows
• Integrated analytics and ticketing

In a world where bots run 24/7, your support systems must be just as intelligent—and just as autonomous.

👉 Explore Radium AI’s capabilities at https://radium-ai.io