Catchpoint introduced advanced Performance and Resilience Monitoring for AI Assistants and Agentic AI systems, designed to proactively identify and prevent performance issues, ensuring the stability of key business operations and customer experiences.
With a track record of monitoring AI infrastructures in collaboration with top-tier technology innovators, Catchpoint offers a unique, industry-leading capability to monitor the full internet stack—going beyond surface metrics to diagnose issues deep within APIs, protocols and technologies. These new features empower organizations to proactively monitor both Agentic AI systems and AI-powered assistants with confidence.
As organizations rapidly adopt generative and agentic AI technologies, such as Microsoft Copilot, OpenAI’s ChatGPT, Perplexity, Claude, Google Gemini, and IBM watsonx, business-critical workflows become increasingly dependent on the uninterrupted performance of AI systems. Any latency, outage, or disruption can severely impact customer experiences and business outcomes —as seen during a recent OpenAI outage which resulted in many systems becoming unresponsive or slow. In the case of this incident, Catchpoint helped a major tech brand detect it and take corrective measures before it escalated, avoiding business impact.
Moreover, according to the Internet Resilience Report 2025, 57% of organizations recognize immediately when AI supporting their critical Tier 1 applications becomes unavailable or slower. However, 27% of companies only become aware of such issues when users complain. “AI can’t fail quietly—and yet, in many organizations, it still does,” the report emphasizes.
Catchpoint’s new capabilities ensure immediate visibility into AI performance, enabling proactive management of disruptions to protect business continuity and customer experience.
AI Assistant Reliability Monitoring enables organizations to proactively detect and resolve issues affecting AI APIs, LLMs, and chatbots. Key capabilities include:
- Global API reachability: Test AI endpoints from key global regions to rapidly detect DNS, routing, or regional outages from thousands of intelligent agents in over 100 countries.
- Latency baselines: Continuously track response times to catch slowdowns before user experiences degrade.
- Synthetic prompt monitoring: Simulate real-world interactions to validate response accuracy and consistency.
- Uptime and error detection: Instantly alert on API downtime, errors, overload conditions, or malformed responses.
- Visual dependency mapping: Get the full context of the entire system or application to understand any component that may be impacting user experience, not only AI.
Agentic AI Resilience Monitoring is designed specifically for complex, autonomous AI workflows that rely on multiple external dependencies, the new capability delivers full-stack visibility and observability across APIs, networks, cloud services, and third-party tools. Features include:
- Third-party API Monitoring: Track stability and latency of critical cloud services, SaaS APIs, and databases.
- Multi-hop Dependency Visibility: Trace the root cause of cascading failures across complex AI workflows.
- CI/CD Monitoring Automation: Automatically integrate monitoring into CI/CD pipelines to test changes in AI infrastructure.
- Cloud Region Resilience: Identify and mitigate risks associated with specific cloud region disruptions and performance issues.
- Global performance testing: from anywhere in the global observability network or private intelligent agents deployed in key locations, data centers, or offices.
“AI assistants and agentic agents are only as reliable as the networks and APIs they depend on,” said Mehdi Daoudi, CEO of Catchpoint. “Our new capabilities give organizations the visibility they need to ensure AI resilience, reduce downtime, and deliver exceptional digital experiences, enabling IT organizations to innovate as they build the future.”
To learn more about Catchpoint’s AI Monitoring solutions, visit the website here.
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