Large Language Models (LLMs) will reshape every business, industry, and consumer experience, but only if the models, tools, and infrastructure are easy to use and available to everyone. The advantages of artificial intelligence need to be equitably spread to the use cases, problem sets, visions, and new ideas as varied and diverse as we all are. For this to be realized, we have to reframe how information and data are processed and retrieved; a mission Metal – a platform for creating AI-powered applications – is dedicated to achieving.

We are thrilled to announce our participation in Metal’s Seed Round, led by Swift VC and with support from Y Combinator.

The team is building a production-ready, fully-managed, artificial intelligence and machine learning developer platform that includes:

• Data transformation, indexing, and storage

• Easy-to-use APIs and developer-friendly tools to query and consume data

• Vectorized semantic search and embedding fine-tuning

• Observability for applications usage and performance

The aim is usability. With Metal, developers can implement AI applications without writing their own infrastructure, indexing pipelines, or model deployments. You just need a Metal account and an API key.

We envision AI as a technology that benefits everyone, rather than winner-take-all or monopolized by a select few. Metal paves the way for wider access to large language models, making them easier to use, more bespoke, and more intuitive. With developers and enterprises able to leverage Metal's infrastructure, we believe everyone wins.

Meet the team

Metal’s co-founders Taylor Lowe, James O'Dwyer, and Sergio Prada bring distinct skills and leadership to the team. Taylor has years of product management experience. James and Sergio, both engineers, offer deep technical expertise. Together, they offer an in-depth understanding of the challenges posed by building and implementing machine learning infrastructure.

This team is seasoned builders; having a proven track record of successful startups. They met while working at Kustomer, a customer service CRM platform that Meta acquired for $1 billion. Beyond this achievement, they have proven experience from their time at leading tech companies, including Meta, Spotify, Datadog, Carta, and Sprig.

Where can you learn more?

If you are a developer building large language models, or a company looking to leverage the potential of LLMs to extract value from your data:

• Check out Metal’s website

• Read the documentation on their Github GetMetal

• Follow Metal’s Twitter @Metal_io.

Or you can reach out to the team directly on Twitter DMs: Taylor, James, Sergio.

We’re thrilled for the team and look forward to being a part of Metal’s journey!