Final Year Engineering Major Project · Healthcare SaaS

AI-powered tinnitus care that feels ready for real clinical workflows.

TinniCare AI combines machine-learning severity prediction, explainable symptom analysis, Gemini-based care planning, therapy workflows, patient monitoring, and doctor support in one secure platform.

Multi-user authentication
Role-based dashboards
Accessible dark mode
Premium healthcare analytics dashboard showing tinnitus monitoring charts

Latest model output

Moderate · 87% confidence

XAI ready

Complete platform modules

Designed as a full SaaS product: patient workflows, clinician review, persistent records, and production-quality UI states.

Explainable ML severity prediction

Symptom inputs become transparent severity bands with feature contribution scoring.

Gemini care planning

A backend Gemini workflow can generate personalised care plans from structured assessment data.

Long-term monitoring

Patients log loudness, sleep, stress, mood, and notes for trend-aware healthcare review.

Doctor collaboration

Patients share scoped access codes so clinicians can review trends and send secure notes.

From symptoms to action

A patient can complete an assessment, receive an explainable prediction, track daily health, generate a Gemini care plan, and collaborate with a doctor.

Assess

Capture symptom burden, loudness, sleep, stress, anxiety, and therapy adherence.

Treat and monitor

Recommend therapy protocols, measure adherence, and trend outcomes over time.

© 2026 TinniCare AI. Educational healthcare SaaS prototype.

Secure GenMB auth + scoped KV data model.

Built with GenMB
Built with GenMB