Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI by Xiaoshi Dai, Di Xia and Feifan Gao

Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI by Xiaoshi Dai, Di Xia and Feifan Gao is a highly esteemed winner of the very prestigious 2026 Gwobr Haearn A' Design Award in Cynnyrch Digidol Competition Category.

HaearnCynnyrch Digidol· 2026

Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI

by Xiaoshi Dai, Di Xia and Feifan Gao

Client: Sprounix

Gwobr Haearn A' Design Award Winner in Cynnyrch Digidol Category

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The Design

About Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI

Testun Llyfr: Mae Sprounix yn rhyngwyneb wedi'i yrru gan AI sydd wedi'i gynllunio i symleiddio'r broses gymhleth o wneud cais am swydd drwy UX sgyrsiol. Er mwyn datrys problem blinder ceisiadau, mae'r dyluniad yn disodli ffurflenni statig â rhyngwyneb sgwrsio aml-foddol sy'n cipio sgiliau meddal drwy ddeialog naturiol. Mae'r UI yn cynnwys dangosfwrdd Co pilot llifol sy'n darparu hyfforddiant cyfweliad amser real ac olrhain tasgau tryloyw. Drwy integreiddio protocolau Asiant i Asiant, mae'r system yn awtomeiddio trafodaethau cefn-swyddfa, gan ganiatáu i ddefnyddwyr reoli ceisiadau amlder uchel drwy fodel rhyngweithio symlach, di-straen.

The Recognition

About the Gwobr Haearn A' Design Award

Mae Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI yn enillydd Gwobr Haearn A' Design Award, cydnabyddiaeth fawreddog a roddir i ddyluniadau da sydd yn bodloni'r gofynion proffesiynol a diwydiannol a ddisgwylir gan greadigaethau wedi'u dylunio'n dda. Mae enillwyr Haearn yn dangos medrusrwydd mawr, arbenigedd uchel, dealltwriaeth arbenigol a gallu creadigol eu crewyr. Disgwylir i Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI fod yn greadigaeth uchel ei bri, a edmygir ac a anwylir, sydd yn ymarferol ac yn arloesol. Mae'r dyluniad buddugol hwn o Wobr Haearn A' Design Award yn integreiddio arferion gorau'r diwydiant ac mae ganddo nodweddion technegol cymwys wedi'u cysylltu â gwybodaeth ymarferol a dawn. Parchir Sprounix Swyddogaeth Sylfaenol: Asiant Gyrfa AI am ei drylwyredd ac fe'i dyluniwyd i ddarparu gwelliannau ansawdd bywyd sydd yn helpu i wneud y byd yn lle gwell.

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