AI Agent forProactive Problem Management
Surpassing traditional ticketing and SLA metrics with
proactive Agentic AI for robust IT resilience​
From reactive to preventive.
Toward a ticketless future.
Our AI-powered agents work across perception, reasoning, action, and learning to detect anomalies, correlate events, and continuously evolve predictive models. Move beyond SLAs to XLAs with smarter insights, proactive decisions, and proactive problem management that pave the way for truly resilient IT operations.
Why automate what you can eliminate?
Why automate what you can eliminate? Perception agents identify recurring incidents with known patterns and root causes. Reasoning agents analyze these patterns to uncover systemic issues, enabling teams to eliminate problems at the source—reducing noise, tickets, and toil.Â
Prevent before you react
Predict the next incident before it happens. Detect anomalies, learn evolving patterns, and anticipate recurring problems. Learning agents continuously refine prediction models, while reasoning agents spot prevention opportunities, allowing early action to fully avoid impact.
Get insights before they become problems​
Perception agents analyze vast IT operational data to detect anomalies, correlate events, and surface hidden patterns. These insights act as early warnings, enabling SREs to spot risks, act faster, and prevent disruptions.
Act with context, not guesswork
From generating detailed reports to completing ITSM workflows, action agents handle routine problem management tasks with precision. They deliver proactive alerts with full context, so that action can be taken decisively, not reactively, when issues arise.Â
Resolve smarter, just ask
Engage through a conversational interface to identify recurring issues, uncover root causes, and get guided actions all in real time. No dashboards to navigate, no complex queries — just simple, natural conversations that help you prevent problems before they occur.Â
Empowering AIOps with an Agentic AI platform​
Digitate’s Agentic AI platform can orchestrate multiple AI Agents to get work done and boost productivity with minimal human intervention. ​
- Reduced downtime by proactive issue resolution
- Increased efficiency by autonomous decision making
- Improved resilience by automated incident resolution
- Improved stability by proactive problem management​
Frequently asked questions
How does this AI Agent enable a ticketless future in IT operations?​
The AI Agent reduces dependency on reactive ticketing systems by predicting problems early and identifying them before they happen. It shifts the focus from Service Level Agreements (SLAs) to Experience Level Agreements (XLAs), emphasizing user experience and system stability. By continuously learning, collaborating with human experts, and integrating with ITSM tools, the AI Agent orchestrates self-healing processes that reduce ticket volumes and manual interventions—paving the way for intelligent, ticketless IT operations.​
How does the AI Agent work to detect and prevent issues before they cause disruptions?​
The AI Agent functions through a network of specialized sub-agents—each responsible for tasks like data perception, reasoning, action, and learning. It continuously scans operational data (events, incidents, and human conversations) to identify patterns and recurring issues. Predictive models anticipate potential failures, and the reasoning engine performs root cause analysis to recommend preventive actions. Learning agents ensure the system evolves with changing environments, while action agents trigger remediation workflows—all without waiting for incidents to occur.​
How does the AI Agent adapt to dynamic or constantly evolving IT environments?​
The AI Agent incorporates learning agents that continuously update its models based on real-time data and environmental changes. Instead of relying on static rules, it evolves by incorporating feedback from experts, outcomes of past decisions, and shifting operational baselines. This adaptive capability enables the system to remain effective even as infrastructure, applications, and workloads change rapidly—ensuring long-term relevance and accuracy.​
What role do human experts play in a system powered by agentic AI?​
Human experts are not removed from the loop—they’re elevated into a collaborative role. Through External Augmentation Agents and conversational AI interfaces, the system engages domain experts to validate findings, contribute context, and refine workflows. This symbiotic relationship allows the AI to capture tacit knowledge, improve its predictive accuracy, and evolve best practices. Rather than replacing experts, the AI amplifies their impact by scaling their insights across operations.​
