Machine learning that delivers without months of code
Rapidly build, iterate and deploy models with the first low-code machine learning platform designed to help data teams of all skill levels deliver value faster.
Built by AI leaders from Uber, Google, Apple and Amazon. Developed and deployed with the world’s leading organizations.
High Impact, Low Code Machine Learning
Ship models faster with the first end-to-end ML platform that’s simple enough for beginners and powerful enough for experts.
More Productive Data Teams
A single collaborative platform for the entire data team—from analyst to expert data scientist—that brings together low-code simplicity with expert-level control.
More Machine Learning Use Cases
Tackle any use case—even state-of-the-art deep learning—on any structured or unstructured data with the only platform that grows with your organization.
More Value Across the ML Lifecycle
Deliver more results faster with the AutoML alternative that provides model training, iteration and deployment in an easy-to-use unified ML platform.
The Fastest Way to Go from Data to Deployment
Build Powerful Models in Minutes
We automate the hard stuff like writing complex code so you can move faster. Accelerate ML projects with simplified training on any multi-modal dataset for any use case including state-of-the-art deep learning. Instantly connect data and build your first model with a few lines of code or clicks of a button.
Rapidly Iterate with Complete Control
Manage, compare and finely tune your models with granular-level control. Smart recommendations guide less experienced users while a robust set of tuning options allow experts to change anything from encoders to transformers and beyond.
Operationalize with Ease
Deploy ML applications without being an infrastructure expert. Fully managed and built on Horovod and Ray, Predibase makes it easy to scale models in production for batch or real-time inference. Our adaptive engines right-size compute to meet your project’s needs.
Built on Proven Open Source Technology
Ludwig
Ludwig is a deep learning toolbox to declaratively develop, train, fine-tune, test and deploy state-of-the-art models. Ludwig puts deep learning in the hands of analysts, engineers and data scientists without requiring low-level ML code.
Horovod
Horovod is a distributed deep learning framework that scales PyTorch and TensorFlow training to hundreds of machines. It supports Tensorflow, Keras, Pytorch, Apache MXNet and has been used to productionize deep learning models across industries
Use Cases
Predibase works across any supervised machine learning use case, so if you have labeled or historical data, our platform can learn from those patterns and apply it to use cases such as: