Telmai Data Reliability Agents continuously monitors, validates and enriches data in Microsoft OneLake, delivering high-quality, trusted data to users and AI agents.
Telmai, the AI-powered data observability platform, today announced its partnership with Microsoft to make it easy for Microsoft Fabric users to detect and resolve data quality issues in their lakehouse.
Agentic AI requires low-latency and real-time access to validated, contextual data. This forces a significant shift in how organizations monitor, detect, and resolve quality issues.
Telmai enables data teams to monitor and detect issues as close to the source as possible, maintaining low-latency access to validated, context-rich data, in the Lakehouse for analytics and AI.
“As data architectures evolve toward more composable and agentic systems, ensuring data reliability is no longer optional, it’s table stakes,” said Mona Rakibe, Co-founder and CEO of Telmai. “By validating data at the source and providing real-time trust signals for both humans and AI agents, Telmai ensures data in OneLake is validated, contextual, and explainable.”
Telmai’s integration with OneLake allows users to continuously monitor and validate structured, semi-structured, and unstructured data as it lands, ensuring low-latency access to validated data in OneLake.
Telmai’s engine enables users to implement custom validation checks and alert policies tailored to their business logic, detecting data inconsistencies and anomalies in real-time.
Decentralized Data Trust Across the Fabric Ecosystem
Telmai extends data trust across the Microsoft Fabric ecosystem by leveraging its AI-powered Data Reliability Agents, making data quality insights accessible to both technical and business users across distributed data domains.
These agents allow users to query incidents, interpret anomalies, and deploy data monitors through plain language commands. By providing clear, contextual explanations of root causes of data quality incidents, Telmai accelerates issue resolution and shortens the time between detection and remediation.
This democratized approach reduces reliance on engineering teams and ensures that critical data quality insights remain accessible and actionable for all relevant stakeholders. As a result, enterprises can accelerate time-to-value while expanding trust in data across analytics, governance, and AI workflows within Microsoft Fabric.
“Accurate and trusted data is critical to the success of any analytics and AI project,” said Dipti Borkar, VP & GM of Microsoft OneLake & ISV Ecosystem at Microsoft. “Telmai’s integration with OneLake enables customers to quickly and easily build AI-ready, trusted data products that are reliable, explainable, and scalable.”
Explore AITechPark for the latest advancements in AI, IOT, Cybersecurity, AITech News, and insightful updates from industry experts!