Soulnest Mobilapplikation by Yixuan Song and Jiahui Yu

Soulnest Mobilapplikation by Yixuan Song and Jiahui Yu is a highly esteemed winner of the very prestigious 2026 A' Design Award i Jern in Mobilteknologi, Applikationer og Software Design Competition Category.

JernMobil· 2026

Soulnest Mobilapplikation

by Yixuan Song and Jiahui Yu

Client: SoulNest

A' Design Award i Jern Winner in Mobil Category

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Verified Award Winner
Verify Award Status for #182422

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The Design

About Soulnest Mobilapplikation

Soulnest er en mobilapplikation skabt til at understøtte mentalt velvære. Applikationen tilbyder en kunstig intelligens-ledsager, der guider brugerne gennem fire trin: valg af ledsager, vurdering, terapi og kriselindring. Ansigtsanalyse og pulsmåling gør det muligt for ledsageren at tilpasse sin tone og vejledning i realtid. Kognitive adfærdsterapeutiske metoder anvendes til at hjælpe brugerne med at håndtere følelsesmæssig stress. Al databehandling foregår på enheden, så applikationen fungerer offline og holder personlige data private.

The Recognition

About the A' Design Award i Jern

Soulnest Mobilapplikation er vinder af A' Design Award i Jern, en prestigefyldt anerkendelse, der tildeles gode designs, som opfylder de professionelle og industrielle krav, man forventer af veldesignede skabelser. Jernvinderne viser stor dygtighed, høj specialisering, ekspertforståelse og kreativ kapacitet hos deres skabere. Soulnest Mobilapplikation forventes at være en højt estimeret, beundret og kær skabelse, der er praktisk og innovativ. Dette design, der har vundet A' Design Award i Jern, integrerer branchens bedste praksis og har kompetente tekniske egenskaber knyttet til knowhow og talent. Soulnest Mobilapplikation respekteres for sin grundighed og er designet til at levere forbedringer af livskvaliteten, der er med til at gøre verden til et bedre sted.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Soulnest pioneers a paradigm shift in mental health by replacing traditional high-barrier appointments with an immediate, 4-step stabilization loop. It democratizes emotional care through de-stigmatized Ai avatars, delivering personalized support in under 10 seconds. Engineered for digital equity, it features on-device Ai inference for full offline functionality on low-end devices. Adhering to Wcag standards and low-arousal aesthetics, Soulnest fosters global resilience with proven 72% efficacy.
Dimensions & Packaging: Ai architecture: Green Llm framework optimized via Tensorflow lite for local edge-computing. Performance: On-device inference latency less than 120ms; 40% reduction in peak Cpu load via adaptive computation dimming. Bio-data: Heart rate sampling at 30fps; 100% on-device physiological processing (zero-cloud privacy). Universal equity: Lightweight build less than 150mb for low-end device compatibility. Compliance: Full Wcag 2.1 level Aa and Iso-standard data encryption for global digital wellness.
Tags: Mental Wellness, Ai Companion, Social Impact, Emotional Intelligence, Inclusive Design, Biofeedback, Digital Health, Wearable Interaction, Cbt Therapy, Accessibility
Production Technology: Soulnest implements an empathic interaction system by merging Rppg bio-sensing with Facs-based facial tracking. This transforms passive interfaces into a responsive biofeedback loop, where Ai avatars dynamically adapt their tone and guidance based on real-time physiological stress markers. The design utilizes atomic design systems and flutter for cross-platform fluidity, ensuring a seamless experience that balances clinical rigor with a low-arousal visual language.
Design Challenge: The hardest part was achieving emotional authenticity while ensuring absolute privacy. Internal factors: We had to balance clinical rigor with a low-arousal Ux to prevent digital fatigue. External factors: Overcoming the limitations of on-device Ai inference was crucial to allow full functionality on low-end hardware without cloud dependency. Result: We successfully engineered a responsive bio-feedback loop that senses crisis through subtle physiological cues, navigating complex data-protection laws while delivering life-saving immediacy.
Research: We conducted a multi-modal mixed-methods study to bridge the 75% gap in immediate mental support. Methodology: Using evidence-based design and longitudinal tracking, we integrated Cbt frameworks with Ai interaction. Tools and participants: 1,200 diverse users were monitored via Rppg sensors and biometric wearables over 6 months. Results: Data showed a 72% increase in emotional regulation and a 58% reduction in crisis duration. Impact: The research proves that Ai-driven, bio-responsive tools can democratize mental healthcare, transforming high-barrier therapy into a scalable, stigma-free social infrastructure.
Inspiration: Inspired by the "silent crisis" where 75% of those in need lack mental support due to stigma and cost, Soulnest was born to bridge this gap. We observed that the "waiting period" is the deadliest barrier. Our goal was to create a "seamless emotional infrastructure" that is as natural as breathing. By integrating evidence-based therapy with Ai-driven empathy, Soulnest replaces medical coldness with human-centric warmth, ensuring support is a right, not a luxury, at the very moment of crisis.
Project Duration: The project started in Nov 2024 in San Jose and launched the beta version in Aug 2025.
Operation Flow: 1. Selection: Users choose a personalized Ai companion based on visual aesthetics and emotional affinity. 2. Diagnosis: The Ai assesses mental states by analyzing facial micro-expressions and conversational patterns. 3. Therapy: Users access anytime Ai consultations with avatar using Cbt techniques for immediate emotional support. 4. Crisis relief: Interactive scenarios and sensory healing are triggered to de-escalate emotional spikes. 5. Biometric tracking: Wearable sensors monitor physiological indicators, allowing the Ai to proactively intervene and track long-term wellness trends.
Team Members: Yixuan Song
Jiahui Yu
Xianxi Liao