By SoftServe TeamJun 10, 2020
Healthcare & Life Sciences

Five Steps to Healthcare Consumer Engagement: From Vision to Reality

Better engagement for members and patients is the goal of many health systems and payers. Understanding how to get there is mission-critical.

By SoftServe TeamJun 02, 2020
Data & Analytics

Data Integration in Practice: IPaaS Implementation

Discover the technical aspects of IPaaS implementation for high-level data integration.

By SoftServe TeamJun 01, 2020
DXP
Salesforce
Software Development

CPQ for More Effective Selling

How Salesforce CPQ simplifies complex sales processes for improved efficiency and profitability.

By SoftServe TeamMay 27, 2020
Data & Analytics
IoT, XR, Robotics, AI & ML
Security
Software Development

How Occupancy Detection Works: Methods, Benefits, and Challenges

Learn how to measure building occupancy, explore trending methods, and understand their pros and cons.

By SoftServe TeamMay 13, 2020
Data & Analytics

Data Integration in Practice: How IPaaS Works

How Integration Platforms (IPaaS) resolve major data integration challenges.

By Vitalii BashunApr 27, 2020
Data & Analytics
Google Cloud
IoT, XR, Robotics, AI & ML

Real-World Cases for Smart Analytics with Google Cloud

Use cases for implementing a smart analytics solution with Google Cloud

By SoftServe TeamApr 22, 2020
Healthcare & Life Sciences
IoT, XR, Robotics, AI & ML
R&D

Improving Hand Hygiene: SoftServe’s R&D Demo

Slow the spread of illness by verifying a complete hand wash using AI-enabled camera.

By SoftServe TeamApr 21, 2020
R&D
Software Development

Zephyr RTOS Explained

The Zephyr tool provides a collaborative environment helping to deliver an open source real-time operating system (RTOS).

By Vlad Selotkin , Iurii KobeinMar 31, 2020
R&D

Structured-Light Imaging: A Closer Look

Learn how advancements in structured-light imaging are becoming more prevalent in a wide range of applications.

By Max Druchok, Oleksandr GurbychMar 23, 2020
R&D

Protein-Peptide Docking

Learn more about our end-to-end molecular docking pipeline that combines deep learning and DFT approaches to predict protein-peptide docking.