Today, end-to-end machine learning platform Predibase announced a $12.2 million Series A funding round expansion. The company also released its low-code, declarative ML platform for developers.
Last year’s beta period saw over 250 models trained on the platform. Now that Predibase is generally available, these users can deploy their own large language models (LLMs) instead of using OpenAI’s API. Predibase’s LudwigGPT LLM, named after Piero Molino’s 2019 machine learning suite, will also be available to users.
“ML in internal and customer-facing applications gives every company a competitive edge.” Unfortunately, today’s ML tools are too complex for engineering teams, and data science resources are stretched too thin, leaving the developers working on these projects holding the bag,” said Predibase co-founder and CEO Piero Molino. “Our goal is to make it easy for beginners and experts to build ML applications and deploy them with a few lines of code. Now we can build and deploy custom LLMs.”
Today, the company launched its Data Science Copilot, a system that advises developers on model performance. Predibase is offering a two-week trial of its platform.
Paradigm (a crypto company) and Koble.ai (a tool that helps investors find early-stage investments) are customers.
Predibase, like most startups, will use the funding to expand its go-to-market and platform functions.
Predibase faces increasing competition from AWS, Google, Microsoft, and other low-code and no-code ML platforms and startups. The company claims that its focus on developers and ability to provide easy low-code escape hatches set it apart.