Telmai, the AI-driven data observability platform, unveiled its new Agentic offerings, designed to make enterprise data fully Autonomous-Ready. These capabilities allow agentic AI workflows to communicate, make decisions, and execute actions on real-time, trusted data with minimal human intervention.
With the rise of Agentic AI, the demands on enterprise data management have shifted dramatically. Because AI agents require low-latency access to validated information, organizations must ensure data quality at the source, rather than relying on downstream checks, where most companies focus their efforts today. However, validation alone does not suffice. AI agents also need to determine whether data is fit for their specific tasks, which involves embedding contextual metadata into catalogs and semantic layers that agents can readily access. Only when trust and context converge can AI agents operate responsibly and enable enterprises to deploy them with confidence.
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Telmai continuously validates, monitors, and enriches data with quality signals at the data lake level, pushing this metadata for AI consumption. As a result, autonomous AI systems gain a trusted foundation to operate reliably and at scale. With the latest update, AI agents can continuously access not only accurate data but also the crucial data quality context required to automate downstream workflows effectively.
At the heart of this innovation is Telmai’s MCP-compliant server, which enables LLM-powered agents, including Claude, Bedrock, and Vertex, to query data directly. The platform validates structured, semi-structured, and unstructured data while generating comprehensive data quality metadata. Through the MCP layer, AI agents retrieve both validated data and its contextual metadata, eliminating the need for third-party transformations or complex workarounds.
“In the era of model commoditization, true competitive advantage will emerge from trustworthy, dynamic, and contextually aware data,” said Sanjeev Mohan, industry analyst and principal at SanjMo. “Telmai’s latest release is a big step in this process. It offers continuous validation and contextual metadata that enable AI agents to act responsibly, while reducing the operational debt that has long hindered enterprise adoption.”
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Telmai also introduces Data Reliability Agents, a suite of AI assistants accessible through natural language interfaces. These agents democratize data reliability, enabling technical and non-technical users alike to interact with the platform, accelerate decision-making, and gain actionable insights. Furthermore, the agents autonomously detect and remediate data anomalies, provide clear explanations of root causes, and offer recommendations for creating tailored data quality rules. By augmenting automated workflows such as ticket creation and alert triggers, these agents help teams proactively enhance their data quality processes.
“As AI agents take the reins of decision-making, we believe autonomy should never come at the cost of reliability,” said Mona Rakibe, Co-founder & CEO of Telmai. “With these updates, Telmai is laying the groundwork for true intelligent automation and allowing enterprise data teams to shift their focus to driving measurable business value via Agentic AI.”
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