Telmai Raises $5.5 Million n Seed Round

by Kay Aloha Villamor in June 16th, 2023

Telmai, a San Francisco, CA-based data observability platform company built for hybrid data environments, announced that it raised $5.5 million in oversubscribed seed funding.

The round was co-led by Glasswing Ventures and .406 Ventures, with participation from current investors, including Zetta Venture Partners.

The fresh funding will be used to expand its team and meet increased demand for its AI-driven data observability platform.

Telmai offers a cutting-edge data observability platform designed to detect data quality issues and anomalies at the source, ensuring high-quality data before it is ingested into data warehouses and AI models.

Through the utilization of machine learning (ML), Telmai provides a user-friendly interface that enables automatic issue identification for structured, semi-structured, and streaming data sources.

"We built Telmai using a high-scale Spark architecture allowing it to handle the growing volume, velocity, and variety of data in modern enterprises – what our customers call future-proof," said Mona Rakibe, CEO and Co-Founder of Telmai. "Today, by partnering with Glasswing Ventures and .406 Ventures, along with the continued support from our existing investors, we are excited to take the next crucial steps in our company's growth."

Company: Telmai, Inc.

Raised: $5.5M

Round: Seed Round

Funding Month: June 2023

Lead Investors: Glasswing Ventures and .406 Ventures

Additional Investors: Zetta Venture Partners

Company Website:

Software Category: Data Observability Platform

About the Company: Founded in 2020 by Mona Rakibeand Maxim Lukichev, Telmai is a data observability platform company enabling enterprise data owners to monitor and detect data issues in real time. The platform leverages AI to monitor all data passing through the data pipeline before entering the data warehouse, protecting downstream systems and analytics used for decision-making. Telmai's real-time architecture supports anomaly detection closest to data sources and works over complex data types with native support for nested and multi-valued attributes. 


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