Saviant
Building Intelligent Solutions
Overview
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HQ Location
India
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Year Founded
2012
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Company Type
Private
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Revenue
$10-100m
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Employees
51 - 200
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Website
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Twitter Handle
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Company Description
Saviant is the preferred Data Analytics & Intelligent Solutions partner for leading Asset-intensive and Field-force driven Enterprises across industries like Energy, Utilities, Logistics & Construction. We are the trusted Technology Advisors and Implementation Partners for their strategic initiatives around Data Analytics, IoT, Cloud & Mobility. Our teams enable intelligent actions & accelerated business outcomes for our customers across the globe, by defining their Technology Roadmap & Implementation Strategies. Saviant is a Microsoft Gold Partner for Cloud Platform, Data Analytics, Application Development & Xamarin Premier Consulting Partner.
IoT Snapshot
Saviant is a provider of Industrial IoT platform as a service (paas), application infrastructure and middleware, analytics and modeling, functional applications, networks and connectivity, and sensors technologies, and also active in the automotive, buildings, equipment and machinery, food and beverage, healthcare and hospitals, renewable energy, and utilities industries.
Technologies
Sensors
Environmental Sensors
GPS
Humidity Sensors
Others
Pressure Sensors
Temperature Sensors
Utility Meters
Vibration Sensors
Platform as a Service (PaaS)
Application Development Platforms
Data Management Platforms
Device Management Platforms
Use Cases
Functional Areas
Industries
Services
Technology Stack
Saviant’s Technology Stack maps Saviant’s participation in the platform as a service (paas), application infrastructure and middleware, analytics and modeling, functional applications, networks and connectivity, and sensors IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
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
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 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
Data Engineering for enabling Condition Monitoring
The client wanted to deliver a complete sensor-to-software system, that is easy to use with a simple plug-and-measure concept.Each device/sensor has its unique technology, serves a different purpose, and therefore has a separate data acquisition platform that works best for that product. However, their end customers, who are large industrial Enterprises, may need one or multiple devices/products for their applications and therefore need to work with different platforms. There were different data acquisition platforms in use which meant:The client has dozens of hardware & software systems for providing services to their enterprise clientsLarge effort and resources are required to maintain these platformsTime-to-market is also slow & lengthyThe scattered product portfolio leads to a disconnected sales process & low customer perceptionLack of standard Functionality across platforms
Case Study
Real-time Data Engineering for Testing and Monitoring
Sensors capture physical data from equipment at a high frequency which is then managed and analyzed locally on desktop-based systems. Their end users then process the data locally on their desktops and manually create visibility into equipment conditions & their failure modes.They decided to automate data collection and enable cloud-based data processing as well as AI-based fault detection while making it more data-driven instead of age-old rules-based. There were a few challenges to this:Traditional predictive tools are hard to scale and deployNeed predictive analytics to be embedded within their applicationData preparation, cleansing, choosing the right algorithm, training it, and validating needs expertise with modern data platformsThe platform and application need to easily integrate with all hardware products
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Partners.
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.
