Germany-based fitness operator all inclusive Fitness has overhauled its data infrastructure in partnership with data consultancy datasolut and Microsoft distributor ADN, deploying an Azure Databricks environment designed to support machine learning, AI applications, and accelerated business decisions across its nearly 200 studios.
With more than 712,000 members and a studio network approaching 200 locations, all inclusive Fitness had outgrown the data architecture that supported its earlier growth phase. The company has now completed a platform overhaul that consolidates data sources, standardises processing pipelines, and lays the technical foundation for a range of artificial intelligence applications — including a predictive sales engine the company says carries annual revenue potential in the double-digit millions.
The restructuring of the data environment took place in collaboration with Cologne-based specialist datasolut, with ADN — a Microsoft-authorised distributor — providing infrastructure access and enablement support in the background.
At the centre of the new architecture is a Databricks platform deployed on an Azure Landing Zone, structured according to the Medallion architecture principle. This layered design — typically comprising bronze, silver and gold data tiers — introduces clear data quality controls, standardised transformation logic, and consistent governance across all data flows. Legacy ETL and ELT processes distributed across disparate systems have been replaced by unified pipelines, and automated quality checks now run continuously across the platform.
The platform integrates data from multiple internal sources, including the company’s membership database, and makes unified datasets available for both reporting and machine learning workloads. A centralised dashboard provides visibility into Azure and Databricks usage costs, while automated security monitoring operates continuously in the background.
The initial output of this architecture is a machine learning environment in which models can be developed, tested, and deployed in a structured manner. The first major application is what the company describes as an AI-driven sales engine. The system performs churn prediction — estimating the probability that individual members will cancel their memberships — calculates customer lifetime values, and prioritises sales opportunities accordingly. The company has indicated that the economic impact of this application alone represents a potential annual gain in the double-digit million-euro range, though it has not disclosed a specific figure.
Alongside the technical build, datasolut delivered a training programme targeting staff in data analytics and management roles. The objective was to equip internal teams to identify and develop new data use cases independently, reducing long-term dependence on external consultants.
“The decisive factor today is the interplay between architecture, data literacy, and the empowerment of staff. For all inclusive Fitness, we were able to create a platform that is not only scalable but also delivers real value in daily operations,” said Vinzent Wuttke, managing director of datasolut.
From the client side, the platform’s impact is described in operational terms. “Our goal was to consistently align our data strategy with growth. Together with datasolut, we are decisively advancing our starting position — towards faster, data- and information-based decisions,” said Nico Miller, Head of Digital Performance and Member Activation at all inclusive Fitness.
Julian Scholl, Data Scientist at the company, emphasised the structural benefit: “With the new platform, we bring together data sources, business logic, and analytics centrally. This creates a consistent data foundation for the entire company and allows us to develop and deploy reporting, machine learning, and AI solutions significantly faster.”
ADN’s role in the project was described as supporting infrastructure provision and enabling access to Microsoft cloud services, best practices documentation, and supplementary training offerings. The distributor did not lead the technical implementation but provided the partner ecosystem through which datasolut accessed Databricks and Azure tooling.
The measurable outcomes reported by all inclusive Fitness include the ability to integrate new data sources within minutes rather than days, and to bring machine learning models into production within weeks. The company has identified a pipeline of additional use cases to be developed on the platform in the coming months.
Planned applications include next-best-action analyses for the member journey, customer lifetime value prediction models, consolidated business intelligence reporting, AI-assisted location analyses for expansion planning and studio optimisation, predictive maintenance for equipment and investment management, a 360-degree customer view to underpin new service models, and demand forecasting for capacity and workforce planning.
The modular architecture of the platform is intended to enable these use cases to move from concept to production within weeks rather than months, according to the company. The case illustrates a pattern increasingly common among mid-sized consumer businesses: the deployment of cloud-native data platforms not merely as infrastructure upgrades, but as the primary lever for operationalising AI at scale — with the expectation that competitive differentiation will follow from the speed and quality of data-driven decisions.
Dr. Jakob Jung is Editor-in-Chief of Security Storage and Channel Germany. He has been working in IT journalism for more than 20 years. His career includes Computer Reseller News, Heise Resale, Informationweek, Techtarget (storage and data center) and ChannelBiz. He also freelances for numerous IT publications, including Computerwoche, Channelpartner, IT-Business, Storage-Insider and ZDnet. His main topics are channel, storage, security, data center, ERP and CRM.
Contact via Mail: jakob.jung@security-storage-und-channel-germany.de