Modern payment infrastructures have reached a level of complexity where minor technical glitches cascade into significant revenue loss within minutes. As transaction volumes surge and dependencies multiply, IT teams often struggle to manually correlate performance metrics across diverse financial schemes. Iris addresses this by using natural language processing to interpret data, allowing users to query transaction declines, approval rates, and system latency without navigating fragmented dashboards.
IR Launches Iris AI Assistant to Streamline Global Card Payments
Sydney-based observability firm Integrated Research has unveiled Iris for Card Payments, an AI-driven assistant designed to monitor transaction flows in real-time. By integrating directly with the company’s Prognosis platform, the tool aims to reduce the time financial institutions spend diagnosing payment failures and performance bottlenecks across complex global networks.
Built on the foundation of the Prognosis platform—which currently processes over 80 billion transactions annually—the assistant acts as an expert-level filter for raw telemetry. It provides context-aware explanations for system behaviors, effectively lowering the barrier for staff to troubleshoot issues that previously required specialized knowledge. The tool is currently available in beta through the 13.3 release of Prognosis, with plans to expand its diagnostic capabilities into high-value and real-time payment domains in upcoming updates.
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