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SoftServe
For the Future
Overview
HQ Location
United States
Year Founded
1993
Company Type
Private
Revenue
$10-100m
Employees
1,001 - 10,000
Website
Company Description
SoftServe is a digital authority that advises and provides at the cutting-edge of technology. We reveal, transform, accelerate, and optimize the way enterprises and software companies do business. With expertise across healthcare, retail, media, financial services, software, and more, we implement end-to-end solutions to deliver the innovation, quality, and speed that our clients’ users expect.
SoftServe delivers open innovation—from generating compelling new ideas, to developing and implementing transformational products and services.
Our work and client experience is built on a foundation of empathetic, human-focused experience design that ensures continuity from concept to release.
We empower enterprises and software companies to (re)identify differentiation, accelerate solution development, and vigorously compete in today’s digital economy. No matter where you are in your journey.
IoT Solutions
Software Development, Big Data & Analytics, Security, Internet of Things, R&D, Financial Services, Healthcare, Media, Retail, Innovation, Machine Learning, and Experience Design
IoT Snapshot
SoftServe is a provider of Industrial IoT platform as a service (paas), application infrastructure and middleware, analytics and modeling, cybersecurity and privacy, and networks and connectivity technologies, and also active in the electrical grids, finance and insurance, healthcare and hospitals, oil and gas, renewable energy, and retail industries.
Technologies
Use Cases
Functional Areas
Industries
Services
Technology Stack
SoftServe’s Technology Stack maps SoftServe’s participation in the platform as a service (paas), application infrastructure and middleware, analytics and modeling, cybersecurity and privacy, and networks and connectivity 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
Case Studies.
Case Study
Accelerating Digital Transformation for a Global Non-Profit Organization: Rotary International
Rotary International, a global non-profit organization, was facing challenges in keeping up with the rapid pace of digital change and the increasing digital expectations of its members. Despite its focus on global humanitarian and youth leadership development programs, the organization realized that it was falling behind in delivering relevant and reliable digital products. The organization recognized the need to rethink how its digital strategy supported its mission and how it delivered digital products that better focused on evolving member expectations. The challenge was to find a way to leverage digital technologies to enhance member engagement and support the organization's mission.
Case Study
Boosting Oil Production by Optimizing ESP Operating Parameters with AI
Vital Energy, a leading energy company, was seeking ways to increase productivity, lower production costs, avoid downtime, and prevent asset failures. The company's Electrical Submersible Pumps (ESP) played a critical role in their operations, but the manual methods for ESP monitoring and optimization were time-consuming, expensive, and prone to human error. Vital Energy wanted to create an AI-based solution for ESP optimization that would automatically recommend ESP operating parameters, provide visualization of all necessary data, and allow for feedback, input limitations, and operating constraints.
Case Study
Driving Data and Development Efficiency in Healthcare: A Case Study on Provenance Data Systems
Provenance Data Systems (PDS) offers a suite of tools designed for companies to obtain real-time feedback from customers. One of these tools is Pinpoint Feedback, a software solution that enables companies to engage in conversational commerce. PDS aimed to establish a relationship between their applications with a common data platform to break data silos and use the data across various applications. However, they faced several challenges. Firstly, they were struggling with a lack of customer feedback. Secondly, they were unable to implement cutting-edge software, either open-source or SaaS-based. Lastly, they needed data access for the software to run efficiently.
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