The rate of AI development is ushering in a new Moore’s law with the development doubling every few years according to some experts. According to Stanford, the rate of doubling is as frequent as every three months. Irrespective of the actual rate of doubling, the compound growth is exponential and impressive. However, many enterprises that are looking to integrate AI into their workflows have missed the mark by not being able to successfully harness the vast power of AI in product-grade applications as of yet. Metal seeks to resolve this reality with its LLM developer platform that provides organizations with the infrastructure to focus on their business goals without having to worry about building time-consuming internal solutions. The platform handles data connectors, data preparation, indexing, storage, information retrieval, and even observability/memory to ensure queries are being met with the appropriate and accurate response based on past interactions. Any applications looking to externally offer chatbots, search engine capabilities, question and answering, and text summarization can be powered by Metal and quickly. Internally, embeddings or the data that’s being used to power the models can be fine-tuned and even analyzed with clustering, which allows non-technical users to gain insights into patterns and trends within the data. Metal is available on a freemium basis with the developer plan prices at $25/mo per user with custom pricing available for larger and more sophisticated use cases.
AlleyWatch caught up with Metal CEO Taylor Lowe to learn more about the business, the company’s strategic plans, recent round of funding, and much, much more…
Who were your investors and how much did you raise?
We raised $2.5M from Swift Ventures, Chapter One, Y Combinator, as well as friends and family.
Tell us about the product or service that Metal offers.
Metal is a developer platform for LLM applications, with a focus on production-grade applications for enterprise use cases. We’re a fully managed service that removes the complexity of data transformation, indexing, storage, information retrieval, and more so developers can focus on building useful applications. We also offer hands-on support for enterprise customers who want to make their idea for an AI application a reality.
What inspired the start of Metal?
Our founding team has worked together for over 5 years and we always wanted to start a company together. We were inspired to start Metal after living through our own painful experiences of building ML applications, including poor developer experiences, limited abstractions/tooling, and general friction between getting an application live and in front of users. We knew there was an opportunity to make this technology easier to work with and empower the developer community.
How is Metal different?
Metal is built for production-grade/enterprise-ready applications. We are focused on developers who are building LLM applications intended for real-world use.
What market does Metal target and how big is it?
We are targeting enterprise developers but have not yet sized this market given the dynamic nature of the space.
What’s your business model?
We have subscription plans available as well as service engagements for enterprise AI projects.
How are you preparing for a potential economic slowdown?
By keeping our customers happy to give them the confidence and proof of value to stay with us should the economy falter.
What was the funding process like?
It was intense but a lot of fun. It was great to share what we had built in such a short amount of time and the fundraising process was a force function for us to be able to articulate our vision.
What are the biggest challenges that you faced while raising capital?
As an early-stage company, we were just starting to acquire users and revenue.
What factors about your business led your investors to write the check?
What are the milestones you plan to achieve in the next six months?
We’ll use the capital to improve our developer experience – providing more powerful ways to transform, store, and query data in the context of LLM applications. We will also find ways to incorporate structured data into Metal queries. We will also invest heavily in enterprise support – from scaling to data security and compliance.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Focus on delivering value to your customers and being able to prove you’re building something they want. This will give you the most leverage if you need to raise.
Where do you see the company going now over the near term?
We see Metal as the standard for real-world LLM/AI applications. Our mission is to prove this technology can provide immense and transformative value at scale in the enterprise and with the developer community.
What’s your favorite summer destination in and around the city?
Our backyard in Williamsburg NY.