Sprounix Primær funksjon: AI-karriereagent by Xiaoshi Dai, Di Xia and Feifan Gao

Sprounix Primær funksjon: AI-karriereagent by Xiaoshi Dai, Di Xia and Feifan Gao is a highly esteemed winner of the very prestigious 2026 A' Design Award i Jern in Digitalt produktdesign Competition Category.

JernDigitalt produkt· 2026

Sprounix Primær funksjon: AI-karriereagent

by Xiaoshi Dai, Di Xia and Feifan Gao

Client: Sprounix

A' Design Award i Jern Winner in Digitalt produkt Category

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The Design

About Sprounix Primær funksjon: AI-karriereagent

Boktekst: Sprounix er et AI-drevet grensesnitt utviklet for å effektivisere den komplekse søknadsprosessen gjennom en samtalebasert brukeropplevelse. For å løse problemet med søknadstretthet erstatter designet statiske skjemaer med et multimodalt chattegrensesnitt som fanger opp myke ferdigheter gjennom naturlig dialog. Brukergrensesnittet har et flytende Co-pilot-dashbord som gir sanntids intervjuveiledning og transparent oppgavesporing. Ved å integrere Agent-til-Agent-protokoller automatiserer systemet forhandlinger i bakgrunnen, slik at brukere kan håndtere et høyt antall søknader gjennom en forenklet og stressfri interaksjonsmodell.

The Recognition

About the A' Design Award i Jern

Sprounix Primær funksjon: AI-karriereagent er vinner av A' Design Award i Jern, en prestisjefylt anerkjennelse som tildeles gode design som oppfyller de profesjonelle og industrielle kravene man forventer av veldesignede skaperverk. Jernvinnere viser stor dyktighet, høy spesialisering, ekspertforståelse og kreativ kapasitet hos skaperne. Sprounix Primær funksjon: AI-karriereagent forventes å være et høyt ansett, beundret og verdsatt skaperverk som er praktisk og nyskapende. Dette designet, som har vunnet A' Design Award i Jern, integrerer bransjens beste praksis og har kompetente tekniske egenskaper knyttet til kunnskap og talent. Sprounix Primær funksjon: AI-karriereagent respekteres for sin grundighet og er utformet for å gi forbedringer i livskvalitet som bidrar til å gjøre verden til et bedre sted.

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