Functionize

The fight for quality is real: agents ship code faster than you can check it. What you need is another agent, one that answers to you, not to the code.

The models, the data layer, and the execution engine are ours. Built for testing, sharpened on your app.

Every run trains Studio on your app, so coverage sharpens with use.

You set what good means. You make the release call. Studio does the work in between.

An independent agent with no loyalty to your code. Only to the quality of your application.

For the individual raising the bar on quality, one check at a time.

Studio judges how your product runs on models Functionize built for this work, not a general model wrapped in a testing prompt. The difference shows up in three things you can measure.

Studio resolves each element from 200+ data points, with models that carry no other job. A general model does this as one task among thousands

Execution runs on small models built for the work. No step waits on a general model reasoning toward an answer

A wrapped product needs more instruction as flows get complex. Studio needs less, because its models already know how applications behave

Agents interpret what you mean. A machine learning core verifies what your application does. Both halves, one system.