🤖 Baseten: ML to Apps, Instantly
From ML model to full stack app. Shockingly fast
⚾ The Elevator Pitch:
So you've trained a model and now you need to get it into production quickly. Your business users are really excited about the results and have been asking for more data science projects to be completed and for your trained model to launch to production. You want to get it rolled out fast but need to implement all the tedious APIs and UI components - what do you do? The answer is Baseten.
Baseten is an ML Application Builder for data teams. Machine learning has matured at mind-boggling speed. However, there’s still a huge gap between being able to answer a business problem with ML and actually implementing an ML solution. That's because having an ML model sitting on a local computer isn't enough. It needs to be integrated into the business, and that requires infrastructure, APIs, and a front-end for business users. Baseten does all this for it’s users with just a few clicks!
👇 The Drop Down:
Site: baseten.co
Founded: 2019
Stage: Series A
Traction: Several large customers (Patreon, Pipe, Primer, SIL), Full fledged ML solution, self-serve API infrastructure project, used by many data scientists and ML developers
Team: Engineering Leaders and serial Entrepreneurs
Amir Haghighat, Philip Howes, Tuhin Srivastava
🔍 Why we like it
🤖 Easy ML Deployments
Baseten makes it easy to deploy trained models. Data teams can focus on the important work of developing machine learning solutions without having to worry about infrastructure, deployment configurations, or back-end application. This saves time and thus, saves companies money.⚡️ Immediate Interactive Application Use Cases
With just a few lines of code, you can build powerful & auto-served APIs for your machine learning models that give developers immediate access for production use. This seamless procedure makes dev velocity fast and building on ML frictionless.
🤝 Get Involved with Baseten
Check out their website
Join their team! They are hiring
Build with Baseten - check out their API docs