Sifflet, the AI-native data observability platform, has shared an early look at their upcoming system of AI agents designed to help modern data teams scale data quality and reliability, reduce incident response times, and stay ahead of complexity. The new agents extend Sifflet’s core observability capabilities with a new layer of intelligence: Sentinel analyzes system metadata to recommend precise monitoring strategies; Sage recalls past incidents, understands lineage, and identifies root causes in seconds; Forge suggests contextual, ready-to-review fixes grounded in historical patterns. Sifflet’s AI-native approach is already helping customers to handle these workloads with existing functionality. Sifflet’s AI agents address the growing challenge and go one step further by replacing manual triage, alert sprawl, and static rule sets with context-aware automation that augments human teams. Sanjeev Mohan, founder of SanjMo and former VP Analyst at Gartner “Rather than relying on static monitoring, these agents bring memory, reasoning, and automation into the fold, helping teams move from alert fatigue to intelligent, context-aware resolution.” The agentic system is fully embedded in Sifflet’s AI-native platform and will soon be available to select customers in private beta.