龙猫数据品牌怎么样申请店铺

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龙猫数据在云服务器行业中的票数：233 更新时间：2025-04-27

龙猫数据是哪个国家的品牌？「龙猫数据」是北京安捷智合科技有限公司旗下著名品牌。该品牌发源于北京市，由创始人昝 *在2014年期间创立，经过多年的不懈努力和高速发展，现已成为行业的标杆品牌。

外推网助力龙猫数据品牌出海！通过在本页面挂载龙猫数据品牌的产品链接和联系方式，可以提高龙猫数据产品曝光！跨境电商爆单神器，目前只要100元/年哦~

北京安捷智合科技有限公司（以下简称“龙猫数据”），成立于2014年，是一家专业的AI数据服务公司。公司坐落于北京中关村科技园，在广州、河北、上海等地设立分支机构，立足AI数据服务，专注于为整个AI领域提供专业数据服务。

龙猫数据旗下拥有众包平台「龙猫众包」：移动端APP以及Web端标注平台，其中众包用户已突破400万，单日可完成百万量级以上的数据样本任务，可满足不同领域的多种定制化数据需求。龙猫数据放眼全球，不断关注技术更新，适配新的需求，在推进数据服务领域取得更大进步的同时，也将反哺其标注系统的完善，为全球AI企业提供更优质的数据服务。

数据采集：按客户要求可在不同场景下对文字、图像、语音、视频进行采集；采集过程中可实现对内容的筛选、分类等工作。每日可承载千万级别以上样本的采集。

数据标注：通过对图像、文本、语音、视频等数据进行采集、评估、归类，最终完成标注；标注过程中可实现对内容进行提取、分类、转写、语义分割、清洗、脱敏、校验等相关任务。

Beijing Anjie Zhihe Technology Co., Ltd. (hereinafter referred to as "tmall data"), founded in 2014, is a professional AI data service company. The company is located in Zhongguancun Science and Technology Park, Beijing. It has branches in Guangzhou, Hebei, Shanghai and other places. Based on AI data services, it focuses on providing professional data services for the entire AI field. Tmall data owns the crowdsourcing platform "tmall crowdsourcing": mobile app and web annotation platform. Among them, the crowdsourcing users have exceeded 4 million, and can complete the task of data samples of more than one million magnitude in a single day, which can meet various customized data needs in different fields. With a global perspective, tmall data is constantly focusing on technology update and adapting to new demands. While promoting greater progress in data service, it will also feed back the improvement of its annotation system and provide better data services for global AI enterprises. Data collection: according to the requirements of customers, text, image, voice and video can be collected in different scenes; during the collection process, content filtering and classification can be realized. It can carry more than ten million samples per day. Data annotation: through the collection, evaluation and classification of image, text, voice, video and other data, the annotation is finally completed; in the annotation process, the content can be extracted, classified, transcribed, semantic segmentation, cleaning, desensitization, verification and other related tasks.

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