Silent Help
The Quiet Place Between You and the Storm
- Role
- Full-Stack Developer & Designer
- Timeline
- Sep 2024 – Present
- Duration
- Ongoing
- Status
- Live · in development
Silent Help is a privacy-first mental health companion built with pathway intelligence. A living three-tier engine (HIGH, MID, LOW) routes users to the right depth of support for the right moment. Features AES-256-GCM field encryption, offline-first SOS pathways built to open in under 1.5 seconds, and deterministic crisis flows with zero generative AI in high-risk scenarios.
The Problem
Most mental health apps fill silence with noise. People in emotional distress need immediate, judgment-free support — but existing solutions are slow to load, lack proper crisis protocols, and expose sensitive data to AI systems without adequate encryption or privacy safeguards.
The Solution
Built Silent Help as an invisible intervention — a fortress for the mind. The platform uses pathway intelligence to route users to HIGH (crisis), MID (bridge), or LOW (maintenance) support tiers. The SOS pathway is offline-first and pre-rendered for instant access. Every interaction is deterministic when it has to be, generative only when it helps. AES-256-GCM encryption protects all data with PII scrubbing before any AI call.
01 — Features
Key Features
Pathway Intelligence
A living three-tier engine routes you to HIGH, MID, or LOW support — the right depth for the right moment
Privacy by Architecture
AES-256-GCM field encryption, PII scrubbing before any AI call, and strict data sovereignty by default
Crisis-Aware Safety Net
Dual-gate detection swaps in safety cards the instant risk is found, with one tap to trusted crisis support. A designed safety mechanism — not a clinically validated system
Calming Exercise in Under 60s
Breathing exercises, body scan, 5-4-3-2-1 grounding — pre-rendered, offline-first, zero generative wait
02 — Stack
Tech Stack
03 — Challenges
Challenges & Solutions
- 1Building an offline-first SOS pathway with a target load of under 1.5 seconds using pre-rendered crisis resources
- 2Implementing dual-gate crisis detection that swaps in Clinical Safety Cards the instant risk is found
- 3Designing a three-tier pathway engine (HIGH/MID/LOW) that routes users to the right support depth
- 4Achieving AES-256-GCM field-level encryption with PII scrubbing before any AI call
- 5Creating a calming UI designed to make a breathing or grounding exercise reachable within 60 seconds
04 — Role
My Role & Contribution
- Architected the full-stack Next.js application with pathway intelligence routing engine
- Designed and implemented the three-tier support system (HIGH/MID/LOW) with deterministic crisis flows
- Built offline-first SOS pathway targeting a <1.5s load with pre-rendered crisis resources
- Implemented AES-256-GCM field-level encryption with PII scrubbing pipeline
- Created dual-gate crisis detection system with Clinical Safety Card integration
- Designed calming UI with Framer Motion, targeting a calming exercise reachable within 60 seconds
- Integrated semantic journalling with encrypted storage
- Applied GDPR-informed privacy-by-design architecture
05 — Learnings
What I Learned
- •Privacy-by-architecture patterns with field-level encryption and data sovereignty
- •Offline-first pre-rendering strategies for crisis-critical applications
- •Deterministic vs generative AI: knowing when NOT to use AI in high-risk scenarios
- •Designing empathetic interfaces that convey calm through motion and typography
- •GDPR-informed, privacy-first data handling in mental health contexts
06 — Roadmap
Future Improvements
Planning geo-aware crisis line routing, multilingual support, opt-in mood tracking analytics, and integration with professional therapist directories.