Metal Raises $2.5 Million in Funding

by Kay Aloha Villamor in June 27th, 2023

Metal, a New York-based artificial intelligence (AI) startup focused on enterprise applications, raised $2.5 million in a funding round led by Swift Ventures, with participation from Y Combinator and Chapter One.

The funding will be used to expand Metal’s platform for building AI-powered applications and to provide increased support for large enterprise customers.

Metal offers a fully managed platform for developing AI applications using natural language processing (NLP) and large language models (LLMs). The platform handles complex infrastructure like data transformation and storage, allowing developers to focus on creating applications.

Taylor Lowe, CEO and co-founder of Metal, discussed the company’s mission and the impact of its technology during an exclusive interview with VentureBeat. “The success metric for us are live applications that solve problems that can be used by enterprises that can improve people’s lives, and improve the way that people work,” said Lowe. “We want to change the narrative that there’s all this experimentation; we want to see real-world deployments.”

Lowe said that Metal plans to use the seed funding to focus on three areas: building out the core platform and its open-source project, investing in support for the enterprise, and hiring more talent for its team based in Williamsburg, New York. 

Company: Metal Technologies, Inc.

Raised: $2.5M

Round: Unknown

Funding Month: June 2023

Lead Investors: Swift Ventures

Additional Investors: Y Combinator and Chapter One

Company Website:

Software Category: Developer Platform 

About the Company: Founded by Sergio Prada, James O’Dwyer, and Taylor Lowe, Metal is a developer platform that helps engineers deploy machine learning applications. The company focused on enabling teams to build real-world AI products in production. Metal provides easy-to-use APIs and developer-friendly tools for querying and consuming data. Additionally, they offer out-of-the-box features like semantic search and data used for building LLM-powered chatbots. Metal also emphasizes the importance of observability, providing insights into application usage and performance to facilitate learning and iteration.


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