Clean data, train a model, and validate it, no code, nothing sent to the cloud. Built for ML teams of any kind. Works offline.
A quick look at a tabular-data workflow, from raw data to trained model.
Speed, privacy, and skill each block teams with a real dataset from getting to a working model.
Even a simple model can take weeks once you count learning a library, debugging, and waiting on someone else's schedule. That's an efficiency problem, not a science problem.
Leading AutoML platforms are built cloud-first. For sensitive or proprietary data, that's often not an option under compliance or privacy requirements.
Plenty of people have a real dataset and a real question, just not the programming background most ML tools were built for.
Tabular, imaging, signaling, and NLP workflows are all in active beta.
Upload a spreadsheet, clean it, train a model, and validate it, all through a guided interface. No scripts.
In beta Watch demo ▶Classification, segmentation, and detection on image sets, from photos to DICOM files.
In beta Watch demo ▶Sensor data, biosignals, and time-series modeling workflows.
In beta Watch demo ▶Text classification, named entity recognition, and LLM fine-tuning workflows.
In beta Watch demo ▶Every workflow includes the same core toolkit, not just training.
Handle missing values, outliers, and formatting issues through a guided interface before you ever train a model.
Built-in charts and distributions help you understand your dataset before and after cleaning, no plotting library required.
Compare multiple models in parallel in a single session, so you can pick the best performer instead of training one at a time.
Every trained model is saved automatically. Host it locally, or upload and send it to a collaborator directly through the app.
Currently used at two of the top medical institutions in California, teams are training real models on real clinical datasets with Revise.
Choose Revise. AI should be simple. Try it free for 15 days and build a machine learning model without writing a line of code.
Download Revise, sign in with your email, and start building. No card required. Subscribe from inside the app whenever you're ready.
Open Revise and sign in with your email to start your trial.
Renews automatically every month until you cancel. Subscribe from inside Revise during or after your trial. Subscribing mid-trial keeps your remaining free days, and your first charge is when they end. See the Terms.
Tell us about your team and we'll set up your group and send you an access code.
No. Your datasets, models, and results are processed and stored on your computer. The app only contacts our server to sign you in and check your plan, sending your email (at sign-in), an anonymous computer ID, and the app version. See exactly what's sent.
Only to sign in, and to check your plan in the background when you're online. Otherwise Revise works offline. It needs to connect at least once every 30 days to confirm your account. Some imaging and NLP workflows download a public pretrained model the first time you use them.
The next time you open Revise, it asks you to subscribe before you keep working. Your projects and models stay on your computer, so nothing is lost. Subscribe and pick up right where you left off.
Yes. Your subscription renews automatically every month until you cancel, and you can cancel anytime from Manage billing in the app. Revise keeps working until the end of the month you've paid for, and you won't be charged again. If it isn't right for you, email us within 14 days of your first payment for a full refund. Refund policy
Each account works on up to two computers, for example a laptop and a workstation.
One person buys for the whole team. Contact us with your team size and we'll send you an access code. Each member downloads Revise, signs in with their own email, and enters the code.
Revise is built for sensitive data because nothing leaves your machine. You're still responsible for following HIPAA, your IRB protocol, and your institution's policies. Revise is a research and model development tool, not a medical device, and it isn't meant to guide care for individual patients.