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Automated data observability and quality for Data Lake
Telmai is a Data observability and Data Quality platform designed for Open architecture. It monitors data stored/managed in any data system, such as a data lake or data warehouse, in its raw format at scale without sampling
Telmai provides AI-based data observability and quality tooling designed to ensure reliable data across a data lake/lakehouse. It uses data reliability agents to monitor, validate, diagnose, and explain data quality in open architectures.
Telmai deploys Data Reliability Agents that act as the control layer for configurations, metadata, and integrations to automate onboarding and configurations. Validation Agents continuously learn data quality trends to suggest and apply validation rules. Incident Diagnosis Agents analyze anomalies to identify likely causes and dependencies. Lineage Agents map data flows across sources and targets. Data Insight Agents transform raw data into actionable quality insights and summaries. Help Agents provide step-by-step explanations, and Routing Agents direct users to relevant rules, incidents, or assets. The platform continuously validates structured, semi-structured, and unstructured data as it lands in the lake, generating context-rich metadata accessible by agents or catalogs, with natural language interfaces for query and explanation of issues.
Who it’s for: Enterprises with complex data pipelines and multi-source data lakes/lakehouses seeking reliable, AI-assisted data quality and observability across open architectures.
Customers: PropertyGuru Group
Hiring/traction mentions about product tours and customer logos; active blog and product updates; waitlist and demo calls indicate market traction
Started Telmai in November 2020 with a vision to improve data quality. Prior to Telmai spend 5 years at a Data management start-up as director of product management.
Data Science and Engineering Leader with over 15 years of experience in various environments including startups and Fortune 500 companies

Observability for Data Engineering Teams

Open-source monitoring for machine learning models