Train and Deploy Reliable Models on Messy Real-World Data with a Few Clicks

New feature alert: Auto-train & deploy reliable ML models (more accurate than fine-tuned OpenAI LLMs) on messy real-world data — all in just a few clicks!

Common reasons companies struggle to quickly get good ML models deployed and generating business value: messy data full of issues, a need to explore many ML models to train a good one, and infrastructural challenges serving predictions from the model. Now you can handle all of this in minutes using Cleanlab Studio.

For classifying product reviews, the deployed Cleanlab Studio model is more accurate than OpenAI LLMs fine-tuned on the same data. Producing this model merely required a few clicks in the platform which automatically: detect/correct issues in the dataset to produce a better version, identify and train the best ML model for this particular data, and deploy it for serving predictions in an application. Each of these steps typically requires significant code and effort from a team, but not if you use Cleanlab! Within hours, our cutting-edge AutoML with Foundation models produces highly accurate models for almost any dataset.

Cleanlab Studio allows you to rapidly turn raw image/text/tabular data into reliable ML model deployments, by automating all of the necessary steps. No other tool makes the full end-to-end pipeline this easy and performant!

Details on how we achieve this via novel Data-Centric AI techniques and benchmarks of model performance are in our new blogpost: http://cleanlab.ai/blog/model-deployment/