TWAICE Improves Battery Life by 20%, Speeds Customer Onboarding Using AWS


TWAICE provides predictive analytics to help electric vehicle makers and renewable energy firms optimize their use of battery technology. To manage growth driven by rising consumer interest in reducing emissions, TWAICE developed a cloud-native platform built on AWS. The company improved the speed and accuracy of its data analytics by 300 percent, helping customers get the most out of their batteries, as well as cutting battery purchasing and maintenance costs by 20 percent. It also boosted IT team efficiency, reducing development time from several months to 2 weeks, and decreased deployment times from 3 days to a few hours. The time required to onboard customers was cut from weeks to hours and TWAICE was able to maintain the size of its DevOps team, reducing internal costs by 60 percent.  


By building on AWS, we’ve reduced our IT complexity. Now, we can focus on what we’re best at—helping our customers get the most out of their battery technology.”

Jeff Glasson
Chief Technology Officer, TWAICE

TWAICE is bringing an emissions-free future closer to reality. Its cloud-based platform uses predictive analytics and Internet of Things (IoT) to help electric vehicle makers and renewable energy providers optimize their use of battery technology. The company’s customers include major car manufacturers such as Mercedes Benz and Audi, and electricity firms such as Austria’s Verbund. They use TWAICE software to monitor battery condition and performance across their vehicles or energy storage systems.

Using on-premises infrastructure meant it was a slow and expensive process to analyze the large data sets required to deliver insights to customers. So, the Germany-based software startup turned to Amazon Web Services (AWS).

By migrating to the cloud, TWAICE improved the speed and accuracy of its data analytics by 300 percent, helping customers get the most out of their batteries. It also increased the efficiency and innovation potential of its IT team, and cut the time required to onboard customers from 2 weeks to just hours.

Migrating to the Cloud in 6 Months

The company’s cloud-based solution offers insights into battery use that can extend its overall lifecycle by as much as 20 percent. This helps TWAICE improve its service to customers, while also reducing their costs by 20 percent for maintaining and purchasing batteries.

Performing these analytics requires extensive compute power to process large amounts of data, which has increased from 10,000 items a week to several billion a day. TWAICE’s on-premises servers and databases would have made this task slow and expensive, hindering its growth as well as its ability to provide timely and accurate results.

TWAICE began working with AWS in 2020 on multiple workstreams for data migration, its IoT platform, and an analytics pipeline. To speed up the migration, it used an infrastructure-as-a-code approach with AWS Cloud Development Kit (AWS CDK), an open-source software development framework that defined its cloud application resources using familiar programming languages.

Within 6 months, TWAICE completed its migration to the cloud. It was also able to maintain the size of its DevOps team, eliminating the need to hire more people as the business grows. This has cut estimated internal DevOps expansion costs by 60 percent. “Using AWS CDK, it was easy for our team members with a programming background to get up and running quickly,” says Timo Geissler, senior cloud engineer at TWAICE. “It made the journey to the cloud much easier and meant we didn’t have to hire additional people for the transition.”

Using AWS, the company’s IT team is able to develop new battery features much faster using AWS managed services, reducing the need to commit time to infrastructure development. It also reduced deployment times to just a few hours from a 3-day time window.

Faster, More Accurate Battery Analytics

TWAICE can dynamically scale compute capacity in the cloud, which is not only cost-effective, but also produces faster results. Because of the elastic compute capability of AWS, TWAICE can now deliver analytics results in minutes. And by utilizing machine learning techniques, those results are up to 300 percent more accurate than before. “With better analytics, our customers get more precise results. This gives them more trust in their battery systems and helps boost their revenues,” says Jeff Glasson, chief technology officer at TWAICE. “It means we’re more agile too, so we can focus on service improvement. It’s a big win on both sides.”

TWAICE trains its machine learning models to continually improve predictions on battery lifetime. For this, it uses Amazon SageMaker, which helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning models. “We no longer have to build custom solutions for model management or invest in expensive IT equipment to support our analytics,” says Max Forster, senior cloud engineer at TWAICE. “We can run hundreds of machine learning jobs in parallel without having to worry about scaling up the underlying IT setup. Everything just works.”

Reducing Customer Onboarding Times from Weeks to Hours

With consumer interest in electric vehicles and renewable energy sources growing, TWAICE was receiving more and more new customer requests. “Our team was stretched. Each customer had its own code that required each one to be managed individually. This could take up to 2 weeks to process” says Forster.

Now, TWAICE has automated code production and increased IT team efficiency using AWS IoT Greengrass, an open-source edge runtime and cloud service for building, deploying, and managing device software. To handle the IoT certificates required for each battery its customers monitor, TWAICE automatically provisions resources using AWS Lambda, which lets it run code without thinking about servers or clusters.

Making these changes reduced manual intervention and cut onboarding time for customers from up to 2 weeks to just hours, so the company can satisfy customer demand while accelerating growth. Over the past 2 years, TWAICE has increased its customer count by almost 100 percent and the amount of data processed has increased 100,000-fold. And, with a unified IT infrastructure running on AWS, TWAICE can focus on its core business. “By building on AWS, we’ve reduced our IT complexity,” says Glasson. “Now, we can focus on what we’re best at—helping our customers get the most out of their battery technology.”



Based in Germany, TWAICE combines specialized battery knowledge and artificial intelligence to provide detailed and actionable battery insights for its customers. TWAICE provides a predictive analytics platform that eliminates risk around health, safety, and warranty and enables its customers to outperform their peers by saving time and costs while increasing battery performance and lifetime.

Benefits of AWS

  • Migrated to a cloud-native solution built on AWS in 6 months
  • Reduces customer onboarding times from weeks to hours
  • Boosts battery life for customers by 20%
  • Improves efficiency of IT team

AWS Services Used

Amazon IoT Greengrass

AWS IoT Greengrass is an open-source edge runtime and cloud service for building, deploying, and managing device software.

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Amazon SageMaker

Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.

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Amazon Lambda

AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and software as a service (SaaS) applications, and only pay for what you use.

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