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Nextbillion.ai
为全球启用企业 AI 映射解决方案
概述
公司介绍
NextBillion AI 相信集中式地图技术已成为过去。一张地图并不适合所有人。每个客户、用例、地理位置都是不同的,在 Nextbillion AI,我们以前所未有的方式为企业构建自定义地图 API。用于超本地化业务的去中心化、模块化、自定义地图堆栈。他们为企业提供定位工具和 API,帮助他们采用 AI 优先的方法,同时解决所有与地图相关的业务问题
物联网解决方案
提供 AI 平台上的 mapverse 数据,以及可定制的 API 和 SDK。它们为最后一英里配送、远程信息处理、食品配送、叫车服务中的复杂地图应用程序提供支持。该解决方案可定制为超本地化,并针对难以解决的企业用例进行精确定位。
物联网应用简介
Nextbillion.ai 是基础设施即服务 (iaas), 和 应用基础设施与中间件等工业物联网科技方面的供应商。同时致力于运输等行业。
技术栈
Nextbillion.ai的技术栈描绘了Nextbillion.ai在基础设施即服务 (iaas), 和 应用基础设施与中间件等物联网技术方面的实践。
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设备层
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边缘层
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云层
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应用层
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配套技术
技术能力:
无
弱
中等
强
实例探究.
Case Study
Grassdoor Boosts Efficiency and Cuts Costs with NextBillion.ai’s Distance Matrix API
Grassdoor's primary challenge was to calculate accurate ETAs and optimize routes for last-mile and on-demand deliveries. The company needed a Distance Matrix API that could handle large API call volumes at scale, run at high throughput and low latency, and be cost-effective. The existing Distance Matrix APIs in the market had limitations, such as a matrix size limited to 25*25 elements, which was insufficient for optimizing a large number of deliveries for Grassdoor's large-scale operations. The cost of these existing APIs was also a concern as they proved expensive and the problem worsened as Grassdoor scaled up. The company was also looking for ways to improve operational efficiency in terms of increased throughput and reduced latency as they scaled.
Case Study
AI Company Builds Country Scale Maps in 3 Months: A Case Study
A leading AI cloud computing company was faced with the challenge of creating a large scale, end-to-end mapping solution for the entire UAE within a span of three months. The company needed to build high precision, country scale maps with rapid refresh rates, a task that is both expensive and extensive. The process involved building a map at a UAE level, adding 50+ custom attributes, performing quality checks and conflict resolution, and constantly maintaining and refreshing map data. The company also needed to derive map data intelligence from multiple imagery sources, which was a time-consuming process. The data structures used by different routing and navigation engines like OSRM and others vary by routing engine type. The client needed map data that could easily integrate with their existing routing and navigation engines.
Case Study
Enhancing Delivery Efficiency with Custom Mapping Solution: A Case Study on a Top US-Based Food Delivery Company
The leading food delivery company in the US was facing challenges in keeping up with the growing demand and customer expectations. The company was striving to meet its ambitious growth goals without compromising on the quality of service. The existing mapping solutions were rigid and did not cater to the company's specific needs. The company required a more tailored mapping solution that would help them achieve more efficient and on-time deliveries, provide more accurate Estimated Time of Arrivals (ETAs), and reduce costs on Maps APIs.