Tower raises €5.5M to empower data engineers in the AI era

Tower raises €5.5M to empower data engineers in the AI era

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The Berlin-based startup Tower, founded by former Snowflake engineers Serhii Sokolenko and Brad Heller, aims to be the go-to platform for AI-generated data pipelines to run effectively. While creating AI-generated code is becoming easier, ensuring its seamless operation remains a challenge. Tower seeks to bridge this gap by focusing on the practical execution of AI-assisted development tasks, such as testing, debugging, and managing AI-generated code in production environments. The startup has secured €5.5 million (around $6.4 million) in pre-seed and seed funding from investors like Speedinvest and DIG Ventures, along with notable angels in the data infrastructure space.

The platform integrates storage and compute, based on the Apache Iceberg open table format, ensuring compatibility with major data engines and enabling customers to maintain data ownership without being locked into a single ecosystem. Tower supports AI agents utilizing fresh, proprietary data instead of outdated public internet archives.

Tower’s funding includes support from investors like Flyer One Ventures, Roosh Ventures, Celero Ventures, and Angel Invest. Key figures in the data industry, such as Jordan Tigani of MotherDuck and Olivier Pomel of Datadog, are among the angel investors, reflecting the platform’s appeal to data infrastructure veterans.

Tower aims to alleviate the operational burdens of technologies like Apache Iceberg, as noted by Ford Motor Company’s engineering director, Gaurav Saxena. Early traction figures indicate substantial usage, with over 200,000 runs across 30,000 applications and 70,000 monthly downloads of its Python SDK since launch.

According to Sokolenko, Tower’s mission is to transform AI-generated concepts into reliable production systems using unique company data. The startup plans to use its new funding to expand its team and enhance platform capabilities amidst a competitive landscape featuring entities like Snowflake and Databricks. By focusing on closing the gap between AI-generated and production-ready code, Tower hopes to establish itself as a key player in this evolving sector.

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