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Soulnest Celular Aplicación by Yixuan Song and Jiahui Yu

Soulnest Celular Aplicación by Yixuan Song and Jiahui Yu is a highly esteemed winner of the very prestigious 2026 A' Design Award Fierru Premiu in Aparina Kamay Competition Category.


FierruAparina· 2026

Soulnest Celular Aplicación

by Yixuan Song and Jiahui Yu

Client: SoulNest

A' Design Award Fierru Premiu Winner in Aparina Category

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Verified Award Winner

Verify Award Status for #182422

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The Design

About Soulnest Celular Aplicación

Soulnest nisqaqa huk celular aplicaciónmi, yuyay allin kawsayta yanapananpaq ruwasqa. Kay aplicaciónqa huk inteligencia artificial masintam quyku, chaymi ruwaqkunata tawa ruwaykunapi pusan: masi akllay, chanin qhaway, hampiy chaymanta llakiy pisiyachiy. Uya qhawaywan sunqu takay tupuywanqa masiqa rimayninta pusayninta ima chay pachallapi hukchayta atin. Cognitivo conductual hampiy ruwaykunataqa apaykachakun, ruwaqkuna sunqu llakiyninkuta allinta apanankupaq. Tukuy ruwayqa kikin aparatollapim ruwakun, chaymi aplicaciónqa mana internetwan llamkanpas, sapanchasqa willakuykunatapas pakasqata waqaychan.

The Recognition

About the A' Design Award Fierru Premiu

Soulnest Celular Aplicación A' Design Award Fierru Premiu mishak kan, yupaychay, kayta ruray yachak shinallatak industriapak mañaykunata paktachik alli diseñukunaman kun. Fierru mishak kashkakunaka hatun ruray ushayta, hanak yachayta, yachak yuyayta shinallatak ruray kamachiyta rikuchinku. Soulnest Celular Aplicación sinchi yupaychashka, kuyashka shinallatak kuyashka ruray, ruranapak alli shinallatak mushuk yuyaypi kanata munanku. Kay Fierru Premiu japishka diseñuka industriapak ashtawan alli ruraykunata tantachin shinallatak yachaywan shinallatak ushaywan tantashka tekniku ushayta charin. Sinchi ruraymanta Soulnest Celular Aplicación yupaychashka kan shinallatak kawsayta alliyachik ruraykunata kuypak ruray kan, pachata ashtawan alli kachun ruran.

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

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