Most mental health apps try to understand user text with basic keyword matching or generic sentiment analysis. The problem? "I'm fine" from someone with depression carries a completely different signal than "I'm fine" from someone who's actually fine.

Context matters. Patterns matter. Clinical nuance matters.

I trained a classification model specifically on mental health text data — depression, anxiety, stress, crisis signals — because the existing NLP tools weren't built for this domain.

If you're building a therapy app, wellness platform, or any tool that processes user text related to mental health, generic models will fail your users.

MindClassify API gives you a single REST endpoint that actually understands mental health language. Free tier available so you can test it in your pipeline before committing.

Would love to hear what mental health devs are building right now 👇