Hive AI Kunnskapskartleggingsplattform by Hive AI is a highly esteemed winner of the very prestigious 2025 A' Design Award i Sølv in Grensesnitt-, Interaksjons- og Brukeropplevelsedesign Competition Category.
SølvGrensesnitt· 2025
Hive AI Kunnskapskartleggingsplattform
by Hive AI
Client: Hive AI
A' Design Award i Sølv Winner in Grensesnitt Category
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- Verified Award Winner
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The Design
About Hive AI Kunnskapskartleggingsplattform
Hive AI er en kunnskapskartleggingsplattform for studenter, fagfolk og forskere. Plattformen bruker sekskantede kunnskapsnoder for å strukturere fragmentert informasjon til sammenkoblet kunnskap. Brukere laster opp tekst, videoer og bilder, og kunstig intelligens foreslår koblinger, grupperer relatert innhold og identifiserer kunnskapshull. Ikke-lineær navigasjon støtter fri utforskning i stedet for faste spørsmål-og-svar-stier. Visuelle maler, som historiske tidslinjer og tredimensjonale sekskantkart, presenterer kunnskap på en tydelig måte. Et responsivt grensesnitt støtter lyse og mørke temaer.
The Recognition
About the A' Design Award i Sølv
Hive AI Kunnskapskartleggingsplattform er vinner av A' Design Award i Sølv, en usedvanlig prestisjefylt anerkjennelse som tildeles design i toppklassen som er nydelige og imponerende. Sølvvinnere er enormt briljante og usedvanlig kreative verk som viser designernes enestående ekspertise, talent og skarpsindighet. Hive AI Kunnskapskartleggingsplattform forventes å være et praktfullt utstillingsverk som er bemerkelsesverdig profesjonelt og dypt nyskapende. Dette designet, som har vunnet A' Design Award i Sølv, er en svært bemerkelsesverdig, beundret oppfinnelse som gagner og flytter grensene for kunst, vitenskap, design og teknologi. Hive AI Kunnskapskartleggingsplattform er et skaperverk mange misunner, som vekker ønsker, gir positive følelser og vekker undring og forundring.
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- Hive AI is a transformative learning platform that enables learners to build personalized knowledge systems. With the unique “hexagon knowledge nodes” and AI-driven tools like tailored recommendations, knowledge grouping, and dynamic data visualization, Hive supports students, professionals, and researchers in fostering interdisciplinary exploration and managing complex information.
- Dimensions & Packaging
- Designed for adaptability, efficiency, and reliability, the platform features a responsive interface optimized for various screen sizes, supporting landscape and portrait modes. Users can personalize their experience with light and dark themes, while cross-device compatibility ensures accessibility. AI-driven adaptability enhances learning preferences, providing real-time interactions with secure performance. Hive AI integrates technical precision with user-friendly design, delivering a dynamic, intuitive experience tailored to individual needs.
- Tags
- Geneartive AI, Adaptive Learning, Personalization, Ed-Tech, Non-linear Interaction, Data Visualization
- Production Technology
- Hive AI's technology was developed through an iterative, data-driven approach leveraging advanced neural networks. The product mission guided development, ensuring the machine learning framework effectively organizes users' thoughts into structured knowledge. Rigorous testing and refinement perfected the node-based architecture for seamless non-linear exploration. The final system prioritizes adaptability, efficiency, and reliability, empowering users with a dynamic, personalized learning experience.
- Design Challenge
- How can node-based interactions feel as intuitive as conversation-based AI? This challenge explores motion design, iconography, and cognitive flow for seamless user adaptation. By researching existing node-based systems, the effectiveness in guiding eye movement and mental mapping was evaluated, identifying both strengths and gaps. Through user testing, motion and icons for clarity and usability were refined. The goal is to create a visually intuitive, AI-assisted system that preserves familiar interaction patterns while enhancing how users navigate complex knowledge structures with ease and engagement.
- Research
- Type:
Competitive & User-Centered Design Research
Objective:
Enhance exploratory, autonomous learning with AI-powered tools.
Methodology:
Surveys, interviews, and usability testing.
Tools:
Google Forms, SurveyMonkey, Zoom, Figma prototypes.
Participants:
100 technology enthusiasts
Results:
Optimized node connection interactions.
Improved accessibility with refined UI.
Prioritized key data visualization methods.
Insights & Impact:
AI-driven design enhances learning efficiency, accessibility, and critical thinking, fostering a more engaging and effective digital education experience. - Inspiration
- Hive AI epitomizes usability, efficiency, speed, and reliability. Drawing on generative AI and mind-mapping, it transforms learning into a dynamic, personalized journey. Market research shows 78% of users find current tools limiting, revealing a major business opportunity. With elegant simplicity, fluid design, and smart organization, Hive AI redefines learning and unleashes creativity.
- Project Duration
- Research - 1 Month
Concept and Prototyping - 2 Months
Design Finalization - 1.5 Months
Evolutives & APP Development: ongoing - Operation Flow
- The system structures fragmented information into interconnected knowledge. Learners upload and organize content - text, videos, and images - and AI enhances connections and identifies gaps.
- Node Expansion builds knowledge structures based on interests.
- Gap Bridging links concepts for deeper understanding.
Structured Organization groups information for easier memorization.
- Nonlinear Exploration enables dynamic navigation.
Hive AI also provides visual templates, like historical timelines and 3D hexagonal maps, making knowledge presentation more intuitive and effective. - Patents
- Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen
- Team Members
- Yongwen Dai
Xuefei Wang
Keqing (Clara) Jiao
Hanyong Yang
Huiyang Chen - Image Credits
- Yongwen Dai, Xuefei Wang, Keqing (Clara) Jiao, Hanyong Yang, Huiyang Chen
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