Saviant
构建智能解决方案
概述
总部
印度
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成立年份
2012
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公司类型
私营公司
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收入
$10-100m
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员工人数
51 - 200
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网站
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推特句柄
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公司介绍
Saviant 是能源、公用事业、物流和建筑等行业领先的资产密集型和现场力量驱动型企业的首选数据分析和智能解决方案合作伙伴。我们是值得信赖的技术顾问和实施合作伙伴,因为他们围绕数据分析、物联网、云和移动性开展了战略举措。我们的团队通过定义技术路线图和实施策略,为全球客户提供智能行动和加速业务成果。 Saviant 是云平台、数据分析、应用程序开发和 Xamarin 高级咨询合作伙伴的 Microsoft 金牌合作伙伴。
物联网应用简介
Saviant 是平台即服务 (paas), 应用基础设施与中间件, 分析与建模, 功能应用, 网络与连接, 和 传感器等工业物联网科技方面的供应商。同时致力于汽车, 建筑物, 设备与机械, 食品与饮料, 医疗保健和医院, 可再生能源, 和 公用事业等行业。
技术
用例
功能区
行业
服务
技术栈
Saviant的技术栈描绘了Saviant在平台即服务 (paas), 应用基础设施与中间件, 分析与建模, 功能应用, 网络与连接, 和 传感器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
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实例探究.
Case Study
Powering Smart Home Automation solutions with IoT for Energy conservation
Many industry leaders that offer Smart Energy Management products & solutions face challenges including:How to build a scalable platform that can automatically scale-up to on-board ‘n’ number of Smart home devicesData security, solution availability, and reliability are the other critical factors to deal withHow to create a robust common IoT platform that handles any kind of smart devicesHow to enable data management capabilities that would help in intelligent decision-making
Case Study
Transforming Water Utilities with IoT, saving a Billion Gallons every year!
The big problem that Utilities face includes:(i) How to make meters “smart” and ingest the data from homes to the companies and;(ii) how to derive intelligent actions from huge amounts of meter data, in an efficient and cost-effective way.Solving these problems would help Utilities track & monitor water consumption data, identify leakage, theft & various anomalies. This demands the need of a scalable system with remote asset management & proactive maintenance capabilities. This would also help end-consumers understand their water usage for better decision-making to conserve water.
Case Study
Real-time visibility of Supply chain operations with IoT
Food service delivery companies generally manage large volumes of food or non-food products, with very low profit margins. And, one of their major challenges involves optimizing operational efficiency during food delivery, for accelerated business growth and competitive advantage.However, to address this challenge, they had no means to know what exactly happens during the delivery hours. Was the food inventory ready to deliver is kept under optimum temperature conditions? Were the drivers taking the right routes? Was the customer order being delivered on time? Their business required visibility of its supply chain operations in real-time, so they could track & monitor what’s happening every minute. This would help optimize operations and save money.
Case Study
High-end, scalable Cloud based IIoT solution for Device Management & Analytics
Many instrumentation leaders face challenges including how to:Track & monitor their instrument data such as Temperature, Humidity, Dew point or PressureAchieve real-time visibility of data to take necessary measures/actions.Enable Remote Asset management capabilities to keep a watch on the end-devices at pre-scheduled intervalsIntegrate notification engine to alert the end-customers in case of asset failures or abnormal conditions
Case Study
Real-time Data Engineering for Industrial Systems Testing & Monitoring
The UK-based instruments engineering company was facing challenges with their existing system of capturing, managing, and analyzing data from live machines and systems. The sensors installed on various components of industrial equipment like turbines and pumps captured physical data at a high frequency, which was then managed and analyzed locally on desktop-based systems. This resulted in manual, inaccurate, and time-consuming fault detection. The company decided to automate data collection, enable cloud-based data processing, and implement AI-based fault detection. However, they faced several challenges including the difficulty of scaling and deploying traditional predictive tools, the need for predictive analytics to be embedded within their application, the requirement of expertise for data preparation, cleansing, choosing the right algorithm, training, and validation, and the need for the platform and application to easily integrate with all hardware products.
Case Study
Data Engineering for Enabling Condition Monitoring of Industrial Equipment
The instrument engineering company faced a significant challenge in managing the data acquisition from various devices and sensors. Each device or sensor had its unique technology and served a different purpose, requiring a separate data acquisition platform. This led to a scattered product portfolio, disconnected sales process, and low customer perception. The company's end customers, large industrial enterprises, often needed to work with multiple devices or products, which meant dealing with different platforms. This situation resulted in a large effort and resources required to maintain these platforms, and a slow and lengthy time-to-market. The company also faced a lack of standard functionality across platforms.
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合作伙伴.
Supplier
Microsoft Azure (Microsoft)
Microsoft Azure is a Cloud Computing platform and infrastructure created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers. It provides both PaaS and IaaS services and supports many different programming languages, tools and frameworks, including both Microsoft-specific and third-party software and systems. Azure was announced in October 2008 and released on 1 February 2010 as Windows Azure, before being renamed to Microsoft Azure on 25 March 2014.