Tower, a data infrastructure startup, has raised €5.5 million across pre-seed and seed funding rounds to develop its data engineering platform designed for AI-driven systems.
The pre-seed round was led by DIG Ventures, while the seed round was led by Speedinvest with participation from existing investors. Additional backers include Flyer One Ventures, Roosh Ventures, Celero Ventures, Angel Invest, and angel investors such as Jordan Tigani, Olivier Pomel, Ben Liebald, and Maik Taro Wehmeyer. The funding will support product development and expansion of the company’s go-to-market team.
What The Company Does
Tower develops a data engineering platform designed to help organizations build and manage data pipelines and analytical systems used for artificial intelligence and modern analytics workloads.
The platform integrates storage and computing capabilities into a single environment, allowing companies to manage large volumes of analytical data while maintaining control over their infrastructure.
Tower’s system is designed to support data teams responsible for preparing datasets used in machine learning models and AI applications. The platform provides tools for building data pipelines, orchestrating workflows, and ensuring that AI systems operate using current and reliable information.
By consolidating these capabilities into a unified environment, Tower aims to simplify the infrastructure required for organizations to deploy and manage complex data systems.
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Market Context / Industry Background
As artificial intelligence becomes more widely integrated into enterprise operations, companies increasingly rely on high-quality internal data to train and operate AI models.
While public datasets have been widely used in early AI development, many organizations now require systems that can process proprietary business data securely and efficiently.
This shift has increased demand for data infrastructure capable of handling both large-scale analytics and real-time AI workloads.
Open data architectures have become an important part of this trend. These systems allow companies to retain control of their datasets while ensuring compatibility with multiple analytics engines and computing environments.
Tower’s platform is built around Apache Iceberg, an open table format used in modern data lakehouse architectures. This approach allows organizations to maintain compatibility with a wide range of data processing tools while keeping ownership of their data.
Founder / Investor Commentary
Tower was founded by Serhii Sokolenko and Brad Heller, both former engineers at Snowflake.
Sokolenko said recent advances in AI coding assistants have significantly accelerated the development of data pipelines and software systems.
However, he noted that deploying these systems reliably within production environments remains a major challenge for many teams.
According to Sokolenko, while developers can now generate code more quickly with the help of AI tools, organizations still require robust infrastructure capable of running those systems with real company data.
Tower’s platform aims to address this gap by providing an environment where data engineers and AI agents can collaborate to transform AI-generated code into stable production systems.
Growth Plans / Use Of Funds
Tower plans to use the new funding to expand its commercial operations and continue developing its data infrastructure platform.
The company will focus on enhancing its tools for orchestrating data pipelines and managing AI-driven workflows.
Additional investment will also support the expansion of Tower’s go-to-market team as the company seeks to attract enterprise customers working on AI and advanced analytics projects.
By strengthening its platform and expanding its team, Tower aims to position itself as a provider of infrastructure supporting data-intensive AI applications.
About Tower
Tower is a data infrastructure company founded in 2024 that develops tools for managing data pipelines and analytics workflows. Built by engineers with experience at companies such as Snowflake, Databricks, Cloud Dataflow, and Puppet, the platform helps organizations orchestrate data flows, maintain control over proprietary datasets, and support AI and analytics systems. Tower’s architecture integrates data management with pipeline orchestration, enabling teams to deploy data-driven applications more efficiently.
