Sprounix کارگزار هوشمند شغلی by Xiaoshi Dai, Di Xia and Feifan Gao is a highly esteemed winner of the very prestigious 2026 جایزه آهنی A' Design Award in طراحی محصول دیجیتال Competition Category.
آهنمحصول دیجیتال· 2026
Sprounix کارگزار هوشمند شغلی
by Xiaoshi Dai, Di Xia and Feifan Gao
Client: Sprounix
جایزه آهنی A' Design Award Winner in محصول دیجیتال Category
Verified Award Winner
Verify Award Status for #183302The Design
About Sprounix کارگزار هوشمند شغلی
اسپراونیکس یک رابط کاربری مبتنی بر هوش مصنوعی است که برای ساده‌سازی فرایند پیچیده درخواست شغل از طریق یک تجربه کاربری گفتگومحور طراحی شده است. برای حل مشکل خستگی ناشی از درخواست‌های شغلی، این طراحی فرم‌های ایستا را با یک رابط چت چندوجهی جایگزین می‌کند که مهارت‌های نرم را از طریق گفتگوی طبیعی ثبت می‌کند. این رابط کاربری دارای یک داشبورد هم‌خلبان روان است که مربیگری مصاحبه در زمان واقعی و ردیابی شفاف وظایف را فراهم می‌کند. با یکپارچه‌سازی پروتکل‌های عامل به عامل، این سامانه مذاکرات پشت‌صحنه را خودکار می‌کند و به کاربران اجازه می‌دهد درخواست‌های پرتکرار را از طریق یک مدل تعاملی ساده‌شده و بدون استرس مدیریت کنند.
The Recognition
About the جایزه آهنی A' Design Award
Sprounix کارگزار هوشمند شغلی برنده جایزه آهنی A' Design Award است، شناختی معتبر که به طراحی‌های خوبی اعطا می‌شود که الزامات حرفه‌ای و صنعتی مورد انتظار از آفرینش‌های خوب طراحی‌شده را برآورده می‌کنند. برندگان آهن مهارت بزرگ، تخصص بالا، درک کارشناسانه و ظرفیت خلاقانه سازندگان خود را نشان می‌دهند. از Sprounix کارگزار هوشمند شغلی انتظار می‌رود آفرینشی بسیار ارجمند، ستوده و دوست‌داشتنی باشد که کاربردی و نوآورانه است. این طراحی برنده جایزه آهنی A' Design Award بهترین رویه‌های صنعت را یکپارچه می‌کند و ویژگی‌های فنی شایسته‌ای دارد که با دانش عملی و استعداد پیوند خورده است. Sprounix کارگزار هوشمند شغلی به سبب دقتش محترم است و برای عرضه بهبودهای کیفیت زندگی که به بهتر شدن جهان کمک می‌کنند طراحی شده است.
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
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