Infoflow Knowledge Management 企業辦公軟件 by Ying Li, Wei He, Meng Xu and Yang Zhang

Infoflow Knowledge Management 企業辦公軟件 by Ying Li, Wei He, Meng Xu and Yang Zhang is a highly esteemed winner of the very prestigious 2022 A' Design Award 銅獎 in 介面、互動及用戶體驗設計 Competition Category.

銅介面· 2022

Infoflow Knowledge Management 企業辦公軟件

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

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

A' Design Award 銅獎 Winner in 介面 Category

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Colors

The Design

About Infoflow Knowledge Management 企業辦公軟件

Infoflow知識管理係一款企業辦公軟件,用嚟收集、整理同重複使用公司知識。呢個軟件將資訊分類成清晰嘅類別,並根據每位員工嘅職能推薦相關內容。人工智能能夠識別辦公場景,令相關知識可以喺對話或會議中透過單一連結即時打開。用戶可以按關鍵字、路徑或主題進行搜尋。呢個應用程式喺Android、iOS、MacOS同Windows平台上運行,提供一致嘅使用體驗。其目標係減少企業寶貴資訊嘅流失。

The Recognition

About the A' Design Award 銅獎

Infoflow Knowledge Management 企業辦公軟件是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Infoflow Knowledge Management 企業辦公軟件將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Infoflow Knowledge Management 企業辦公軟件出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

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