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Driving Data and Development Efficiency in Healthcare: A Case Study on Provenance Data Systems
Technology Category
- Analytics & Modeling - Machine Learning
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Buildings
- Cement
Applicable Functions
- Product Research & Development
Use Cases
- Building Automation & Control
Services
- System Integration
The Challenge
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.
The Customer
Provenance Data Systems (PDS)
About The Customer
Provenance Data Systems (PDS) is a company that offers a suite of tools designed for businesses to obtain real-time feedback from customers. One of their solutions, Pinpoint Feedback, is not an app but a software solution that leverages communication methods people use, allowing companies to engage in the burgeoning field of 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. They required a technology stack to accommodate the integration of applications and platforms and help them accomplish their business strategy.
The Solution
To overcome these challenges, PDS required an application programming interface (API)-driven solution that did not necessitate intensive engineering to scale and add new applications. They needed a broader pool of resources on an as-needed basis to support a technology stack that aligned with their ongoing business strategy. Specifically, they required a seamless data transfer between applications to collect customer feedback and provide an exceptional user experience for their customers. SoftServe was brought on board to build two products: the PDS platform and its first application. Both the platform and the application had to exchange data via API and integrate into artificial intelligence, cognitive services, machine learning, and multi-channel communication services. SoftServe also built a customer feedback Architecture Roadmap.
Operational Impact
Quantitative Benefit
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