Sprounix AIキャリアエージェント by Xiaoshi Dai, Di Xia and Feifan Gao

Sprounix AIキャリアエージェント by Xiaoshi Dai, Di Xia and Feifan Gao is a highly esteemed winner of the very prestigious 2026 A' Design Award 鉄賞 in デジタルプロダクトデザイン Competition Category.

鉄デジタルプロダクト· 2026

Sprounix AIキャリアエージェント

by Xiaoshi Dai, Di Xia and Feifan Gao

Client: Sprounix

A' Design Award 鉄賞 Winner in デジタルプロダクト Category

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The Design

About Sprounix AIキャリアエージェント

Sprounixは、対話型UXを通じて複雑な求人応募プロセスを効率化するために設計されたAI駆動型インターフェースです。応募疲れの問題を解決するため、本デザインは静的なフォームを、自然な対話を通じてソフトスキルを捉えるマルチモーダルなチャットインターフェースに置き換えています。UIには、リアルタイムの面接コーチングと透明性の高いタスク追跡を提供する流動的なコパイロットダッシュボードが備わっています。エージェント間プロトコルを統合することで、システムはバックエンドの交渉を自動化し、ユーザーがシンプルでストレスフリーなインタラクションモデルを通じて高頻度の応募を管理できるようにします。

The Recognition

About the A' Design Award 鉄賞

Sprounix AIキャリアエージェントは、よく設計された創造物に期待される専門的・産業的要件を満たす優れたデザインに授与される、権威ある評価である A' Design Award 鉄賞の受賞作品です。鉄賞の受賞作品は、制作者の高い技量、高度な専門性、専門家としての理解、創造的な能力を示しています。Sprounix AIキャリアエージェントは、高く評価され、称賛され、愛される、実用的で革新的な創造物であることが期待されます。この A' Design Award 鉄賞を受賞したデザインは、業界のベストプラクティスを統合し、ノウハウと才能に結びついた有能な技術的特性を備えています。Sprounix AIキャリアエージェントは、その徹底ぶりで尊敬され、世界をより良い場所にするための生活の質の向上をもたらすよう設計されています。

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