Learn your labels
Fine-tune a small pretrained model on the examples you already have. Your categories define the task.
Why SotaYard
One task.
A model of its own.
Your team already knows what the right answer looks like. Turn those examples into a specialist model that learns your labels, with evaluation and deployment in the same workspace.
Build your model
Measure before you ship
See results on held-out examples, compare a baseline, and inspect errors before a model can go live.
Put it to work
Deploy a qualifying version to an authenticated API. Try it in the playground and flag uncertain results for review.
Keep improving
Save corrections, export new examples, and train another version. Roll back to a previous deployment when you need to.
Made for a specific decision
What should your
model decide?
Start with one repeatable classification task and examples of the answers you want.
Customer support
Send each request to the right team.
Learn the difference between billing, account access, and technical issues from requests your team has already labeled.
Operations
Keep your records organized.
Categorize incoming text and structured records using the labels and examples that reflect how your business works.
Product
Recognize what a message is asking.
Classify feedback or incoming messages by intent. Send uncertain predictions to review instead of treating every answer as certain.
A result you can inspect
See the evidence.
Then put it to work.
A completed training run is only the beginning. Review accuracy, coverage, class-level errors, and a baseline comparison. Only a model that meets your chosen requirements can be deployed.
After deployment, collect corrections and train a new version. Your current endpoint keeps serving while you evaluate the next candidate.
See how it works
Give your data
a job to do.
Start with your own labeled examples, or try the sample dataset. Train, evaluate, and serve a text classification model in one workspace.
Start building free