I Built an AI Matching System for Pet Therapy Sessions — Here's What the Data Actually Showed

I know, I know — another "I used AI to solve X" post. But hear me out. I've been obsessing over a question for the past few months: Can AI actually quantify the mental health benefits of animal-assisted therapy? Not just say "pets are good for you" (we all know that), but actually measure it, model it, and build something useful around it. This post is about what I built, what I learned, and the surprisingly emotional journey of training a model on behavioral data from real therapy sessions. The Problem With Pet Therapy Today Animal-assisted therapy (AAT) has decades of research behind it. Reduced cortisol. Lower blood pressure. Improved outcomes for anxiety, PTSD, autism, dementia. The data is solid. But the matching process? Still largely manual. A coordinator talks to a patient, talks to a handler, makes a judgment call. It works — but it doesn't scale, and it misses things. I wanted to build a smarter matching layer. The Data I scraped (with permission) session notes, patient intak