ai mental health companion · flutter, onnx, ml kit
MindHeal
An AI mental-health companion that reads emotion on the device, so nothing personal has to leave the phone.
Overview
Private by construction
On-device intelligence, not a cloud round trip
MindHeal runs emotion recognition locally with ONNX Runtime and Google ML Kit, then wraps the result in mood tracking, journalling and guided support. Because inference happens on the device, the sensitive part of the experience works without shipping a face or a voice to a server.
How it was built
- 01Discovery
Starting from what must never leave the phone
Mental-health data is the kind you design around, not for. I drew the privacy line first — inference on-device, nothing sensitive synced — and every later decision had to fit inside it.
- 02Development
Fitting a model into a mobile budget
Getting an emotion model to run smoothly inside a Flutter app meant working within a real memory and latency budget: quantised ONNX models, ML Kit for camera-side detection, and inference kept off the UI thread so the interface never blocks while a frame is processed.
- 03Strategy
A companion, not a diagnosis
The product deliberately stays supportive rather than clinical. Model output feeds reflection and tracking, and the copy throughout is careful never to present a prediction as a verdict about the person using it.
Project details
- Role
- Product design and development
- Type
- AI mobile application
- Stack
- Flutter, ONNX Runtime, ML Kit
The Result
A companion app where the AI work happens on the device it belongs to — responsive in the hand, and private without asking the user to trust a server.
Want something like this built?
Tell me what you have in mind and I will come back with a plan, a timeline and a price.