Xiaoshi Dai, Di Xia and Feifan Gao 嘅作品 Sprounix AI 職業代理

由設計師 Xiaoshi Dai, Di Xia and Feifan Gao 創作嘅 Sprounix AI 職業代理係備受推崇嘅 2026 A' Design Award 鐵獎得獎作品，獲獎類別為數碼產品設計。

鐵數碼產品· 2026

Sprounix AI 職業代理

由 Xiaoshi Dai, Di Xia and Feifan Gao

客戶: Sprounix

數碼產品類別嘅 A' Design Award 鐵獎得獎者

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經驗證嘅獲獎者

驗證設計 #183302 嘅獲獎狀態

訪問網站喺 A' Design Award 查看新聞稿獎項徽章

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設計

關於 Sprounix AI 職業代理

Sprounix 係一個以人工智能驅動嘅介面，透過對話式用戶體驗嚟簡化複雜嘅求職申請流程。為咗解決申請疲勞嘅問題，呢個設計以多模態聊天介面取代靜態表格，透過自然對話捕捉軟技能。介面採用流暢嘅副駕駛儀表板，提供即時面試指導同透明嘅任務追蹤。透過整合代理對代理協議，系統將後端協商自動化，令用戶可以透過簡化、無壓力嘅互動模式嚟管理高頻率嘅申請。

榮譽認可

關於A' Design Award 鐵獎

Sprounix AI 職業代理是 A' Design Award 鐵獎得主，這是授予滿足人們對設計精良的創作所期待的專業與工業要求的優良設計的聲望認可。鐵獎得主展現出其創作者的高超技藝、高度專業化、專家級的理解力和創造能力。預計Sprounix AI 職業代理將成為一件備受推崇、令人欽佩且被珍愛的創作，既實用又創新。這件贏得 A' Design Award 鐵獎的設計整合了行業最佳實踐，並擁有與專業知識和才華相結合的稱職技術特性。Sprounix AI 職業代理因其嚴謹而受到尊重，旨在提供有助於讓世界變得更美好的生活品質改善。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: 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.
尺寸同包裝: 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.
標籤: AI Career Agent, Agent2Agent, Conversational UI, UX Design, Future of Work, Automated Recruitment, NLP, Multi-modal Interaction
生產技術: 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.
設計挑戰: 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.
研究: 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.
靈感: 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.
項目時長: 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.
操作流程: 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.
團隊成員: Xiaoshi Dai
Feifan Gao
Di Xia
圖片來源: Image & video design: Xiaoshi Dai, Di Xia, Feifan Gao