Telmai's Data Reliability Workload Now Generally Available on Microsoft Fabric

Telmai, an AI-powered data observability platform, has announced that its data reliability workload is now generally available on Microsoft Fabric. This move aims to help organizations automate data observability and quality across the Fabric ecosystem.

The workload provides a shared, consistent view of data health across the ecosystem, enabling both human teams and data agents to reason, act, and deliver real business value. It does this by automatically identifying and prioritizing business-critical assets across all workspaces in OneLake Catalog, and then deploying AI agent-monitors that track volume, schema, freshness, and completeness for Delta Lake and Apache Iceberg tables.

This integration addresses the growing need for real-time trust signals across analytics and AI systems. As Mona Rakibe, Co-founder and CEO of Telmai, stated, 'Quality checks that sit outside the platform are always one step behind the data.' With Telmai's workload running natively in Fabric, teams can now answer 'is this data safe to use?' at the moment an agent asks, instead of after the damage shows up downstream.

The reliability layer and intelligence layer work together to provide context-driven observability. Trust signals are exposed in real-time via MCP server, enabling any Fabric data agent or external AI client to query data health, freshness, and incident state before taking action on a dataset. This integration keeps critical data-quality context accessible to every team and workflow that depends on it, without adding infrastructure or operational overhead.