Sprounix Setsi sa Mosebetsi sa AI by Xiaoshi Dai, Di Xia and Feifan Gao

Sprounix Setsi sa Mosebetsi sa AI by Xiaoshi Dai, Di Xia and Feifan Gao is a highly esteemed winner of the very prestigious 2026 Moputso oa Tšepe oa A' Design Award in Moralo wa Sehlahiswa sa Dijithale Competition Category.

TšepeSehlahiswa sa Dijithale· 2026

Sprounix Setsi sa Mosebetsi sa AI

by Xiaoshi Dai, Di Xia and Feifan Gao

Client: Sprounix

Moputso oa Tšepe oa A' Design Award Winner in Sehlahiswa sa Dijithale Category

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The Design

About Sprounix Setsi sa Mosebetsi sa AI

Sprounix ke sebopeho sa marang-rang se tsamaisoang ke AI se etselitsoeng ho nolofatsa ts'ebetso e rarahaneng ea kopo ea mosebetsi ka UX ea moqoqo. Ho rarolla bothata ba ho khathala ha kopo, moralo o nkela libopeho tse sa fetoheng sebaka ka sebopeho sa puisano sa mekhoa e mengata se hapang tsebo e bonolo ka puisano ea tlhaho. UI e na le dashboard ea Co pilot e phallang e fanang ka koetliso ea lipotsoliso ka nako ea sebele le ho latedisa mesebetsi ka tsela e hlakileng. Ka ho kopanya li-protocol tsa Agent ho ea Agent, sistimi e iketsetsa lipuisano tsa morao, e lumellang basebelisi ho laola likopo tse phahameng ka mokhoa o nolofalitsoeng, o se nang khatello ea maikutlo oa ts'ebelisano.

The Recognition

About the Moputso oa Tšepe oa A' Design Award

Sprounix Setsi sa Mosebetsi sa AI ke mohapi oa Moputso oa Tšepe oa A' Design Award, kananelo e hlomphehang e fuoang meralo e metle e finyellang litlhoko tsa porofeshenale le tsa indasteri tse lebelletsoeng ho lintho tse hlahisitsoeng tse entsoeng hantle. Bahapi ba Tšepe ba bontša bokhoni bo boholo, bokhethehi bo phahameng, kutloisiso ea litsebi le bokhoni ba boqapi ba baqapi ba bona. Sprounix Setsi sa Mosebetsi sa AI e lebelletsoe ho ba ntho e hlahisitsoeng e hlomphuoang haholo, e ratoang le e ratehang, e sebetsang le e nang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Tšepe oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa ea indasteri mme o na le litšobotsi tsa theknoloji tse nang le bokhoni tse amanang le tsebo le talenta. Ka lebaka la botlalo ba eona, Sprounix Setsi sa Mosebetsi sa AI e tšoanelehela tlhompho mme e entsoe ho fana ka ntlafatso ea bophelo e thusang ho etsa hore lefatše le be sebaka se molemo.

Behind the Design

Press Kit

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

Unique Properties: Sprounix is a chat-centric AI Career Agent that transforms job seeking into a multimodal interactive journey. Beyond static resumes, it uses text and video dialogue to uncover soft skills and aspirations. A key innovation is the Agent2Agent A2A technology, enabling the user’s agent to communicate directly with recruiter systems for hyper-efficient matching. It also provides automated applications and real-time interview coaching, acting as a proactive career advocate.
Dimensions & Packaging: Sprounix is a cloud-based, responsive web platform compatible with all modern browsers. It supports multi-modal inputs including WebRTC video, voice-to-text, and PDF parsing. The matching engine achieves over 85% accuracy by moving beyond keywords to multi-dimensional intent recognition. The system adheres to WCAG 2.1 accessibility and enterprise-grade security standards, ensuring full GDPR compliance for encrypted candidate data protection.
Tags: AI Career Agent, Agent2Agent, Conversational UI, UX Design, Future of Work, Automated Recruitment, NLP, Multi-modal Interaction
Production Technology: Built on a robust AI infrastructure using Large Language Models (LLM) for natural language understanding and multi-modal analysis. The core innovation is the Agent2Agent (A2A) communication protocol that streamlines data exchange between independent AI entities. The system features a responsive React-based front-end for seamless cross-platform use, integrated with real-time video processing and scalable microservices to handle high-frequency job matching and data sync.
Design Challenge: The primary challenge was designing a seamless UX for the complex Agent2Agent backend. We had to ensure users felt in control while their AI agent performed proactive tasks like autonomous applications. We solved this by creating a highly intuitive, chat-first interface that provides transparent "Co-pilot" updates. Integrating multi-modal inputs (text and video) while maintaining a consistent, supportive AI persona across all platforms was a significant technical and design obstacle we overcame.
Research: Our research explored the Job Search Anxiety among early career talents and the inefficiencies of keyword-based recruitment. We used a mixed-methods approach, including more than fifty user interviews and data analysis of traditional ATS systems. The results showed that users provide forty percent more detailed skill data via natural dialogue than static forms. This led to the development of our Chat-centric discovery interface and the Agent2Agent matching protocol, which proved to reduce initial screening time by seventy percent in pilot tests.
Inspiration: The inspiration came from the challenging labor market faced by Gen Z. Traditional job hunting is often repetitive and discouraging. We wanted to create a "Co-pilot" that doesn't just list jobs but actively advocates for the user. By combining AI-driven matching with a friendly, gamified experience, we aimed to lower the anxiety of career-starting and make professional growth feel like a guided, empowered journey.
Project Duration: The project conceptualization started in January 2025 in the United States. Following intensive research and UX prototyping of the conversational engine, the beta version of the platform was developed and finalized in late 2025.
Operation Flow: The experience centers on a conversational interface where users engage with the AI via text or video. This chat-first approach replaces traditional forms, building a deep professional profile. Once the agent understands the candidate's goals, it leverages A2A protocols to negotiate with recruiter agents and automate applications. The co-pilot remains active throughout, providing instant feedback and resume tailoring via a fluid UI.
Team Members: Xiaoshi Dai
Feifan Gao
Di Xia
Image Credits: Image & video design: Xiaoshi Dai, Di Xia, Feifan Gao