Infoflow Knowledge Management 企业办公软件 by Ying Li, Wei He, Meng Xu and Yang Zhang

Infoflow Knowledge Management 企业办公软件 by Ying Li, Wei He, Meng Xu and Yang Zhang is a highly esteemed winner of the very prestigious 2022 A' Design Award 铜奖 in 界面、交互与用户体验设计 Competition Category.

铜界面· 2022

Infoflow Knowledge Management 企业办公软件

by Ying Li, Wei He, Meng Xu and Yang Zhang

Client: Baidu Online Network Technology (Beijing) Co., Ltd

A' Design Award 铜奖 Winner in 界面 Category

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Verified Award Winner

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The Design

About Infoflow Knowledge Management 企业办公软件

Infoflow 知识管理是一款用于沉淀、整理与复用企业知识的企业办公软件。该软件将信息归入清晰的分类体系，并依据每位员工的岗位角色推荐相应内容。人工智能可识别办公场景，因此相关知识能够通过单一链接直接从对话或会议中打开。用户可按关键词、路径或主题进行检索。该应用可在 Android、iOS、MacOS 与 Windows 上运行，并保持一致的使用体验。其目标在于减少企业宝贵信息的流失。

The Recognition

About the A' Design Award 铜奖

Infoflow Knowledge Management 企业办公软件是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Infoflow Knowledge Management 企业办公软件将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Infoflow Knowledge Management 企业办公软件出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: As enterprise data is growing at an annual rate of 42.2% with 68% not being utilized, the valuable enterprise information can be easily lost, impeding the enterprise’s innovative development. With this design, we hope to provide enterprises and employees with structured information and new experience of knowledge acquisition through intelligent information classification, match information accurately with employees’ roles and office scenarios, and improve efficiency of valuable information use
Dimensions & Packaging: Universally applicable to all models including Android, iOS, MacOS and Windows and all sizes
Tags: Enterprise office, AI, user experience, UI design, design system, office system, knowledge management
Production Technology: The app is universally applied to Android, iOS, MacOS and Windows. Consistent experience is provided for different terminals depending on multiple AI technologies
Design Challenge: Current enterprises mainly rely on traditional management software and full-time staff for information management. Now we face two main challenges. Deeply integrate AI in product design, and integrate and distribute enterprise information in a more systematic manner, to improve the efficiency of data query. Associate knowledge with specific scenarios based on personas, and allow any member to study new knowledge quickly and easily in multiple scenarios
Research: We have conducted user research through questionnaire and interview for enterprise users of different roles and functions. In this way, we not only understand enterprise employees’ pain points in knowledge production and accumulation, but also deeply explore the habits of information organization and application in work against important functions
Inspiration: Embodying the future trend of digital office, it provides solutions for enterprises to accumulate and reuse high-value information based on AI technologies. It improves the utilization of enterprise data by means of clear information classification and personalized knowledge recommendation; and inspires enterprises’ sustainable knowledge accumulation capacity based on identification and conversion of work data. It enables employees to enjoy the benefits of the digital era fairly and efficiently.
Project Duration: The project was launched in early 2021 and the released version was available in September 2021. The software is updated online. The development team are in Beijing.
Operation Flow: Featuring structured information classification and rich content display, it helps users search for knowledge conveniently and flexibly through keywords, paths and themes. It recommends information based on employees’ profiles, enabling users to view and acquire relevant knowledge accurately. It identifies office scenarios based on AI technologies, so users can study new knowledge rapidly and easily by clicking a link in a conversation, meeting or other working scenario
Team Members: Ying Li,Wei He,Meng Xu,Yang Zhang,Xiying Wang,Junjie Huang
Image Credits: Copyrights belong to Baidu Online Network Technology (Beijing) Co., Ltd.2020