From AI Adoption to AI Growth: indasys Builds New Business Opportunities with Lenovo TruScale Infrastructure as a Service

indasys IT Systemhaus AG identified a business opportunity in addressing AI adoption challenges for organizations, including data security, compliance, and scalable infrastructure. To address these, the company deployed a private-cloud AI platform using Lenovo TruScale Infrastructure as a Service (IaaS) in collaboration with Lenovo and NVIDIA. The platform provides a scalable, locally controlled foundation for AI, supporting indasys’ internal operations, its localized cloud offering BaWü Cloud, and its new AI subsidiary Agentum GmbH. Lenovo TruScale allows indasys to scale capacity as demand grows without significant upfront infrastructure investments.

indasys expanded its AI use beyond internal operations to create new AI services for customers, requiring a high-performance platform capable of supporting both internal workloads and commercial services. The company needed greater control over where AI data and workloads are hosted and processed, particularly for customers handling sensitive or regulated data. This led to a strategy focused on locally controlled private-cloud and on-premises deployment options, combined with scalable capacity and flexible infrastructure investment models.

The resulting AI platform integrates Lenovo ThinkSystem servers, Intel Xeon 6 processors, NVIDIA L4 Tensor Core GPUs, and Lenovo storage to deliver accelerated performance for AI workloads while keeping data-intensive applications on local private-cloud infrastructure. Lenovo Professional Services supported the platform’s implementation, helping establish best practices and turn the design into an operational AI environment. The platform enables indasys to run AI applications in a locally controlled private-cloud, supporting both its own use cases and customer services delivered through Agentum GmbH and BaWü Cloud.

indasys is already realizing value from the platform in two key areas: improving internal operations and providing proven AI use cases for customer projects. The company increased its capacity to bid for public-sector tenders sixfold using AI analytics, submitting over 150 AI-supported bids with a 32% win rate. AI analytics also optimize support operations by automating task scheduling and improving real-time visibility into engineer availability, enhancing resource efficiency and customer response times.