Welcome to d-fine

A d-fine team works with the asset manager's experts to develop the new application based on cloud-native technologies and modern platform and software architecture.

The joint team uses an agile approach to development in order to respond quickly and consistently to unexpected situations and complications during the project.

The rigorous quality assurance of the new platform is demonstrated by a multi-stage CICD process with well-defined quality gates and a high degree of automation.

The newly developed energy system model allows consistent planning of the power grid with coupled energy sectors.

Our circuit optimization tool ensures that the power grid remains stable even with many simultaneous construction activities.

The integrated data budget enables new insights from data analysis. 

The hybrid IT architecture links the cloud-based platform with servers on-premise. 

The key factor for project success is our combination of energy industry expertise and professional IT know-how.

We developed a traffic simulation as the basis for the tool.

Different data, such as track infrastructure data and real-time information, were processed into ETL processes.

The tool's decision-making is based on reinforcement learning, for which we developed corresponding agents, states, rewards, and actions.

In regular exchange formats with the dispatchers, further features of the tool were jointly developed and implemented in a later step.

As a basis for optimizing drug storage and supply, heterogeneous internal data was linked with publicly available data using Natural Language Processing.

Based on identified locations and quantities, a robust framework that is meaningful even with limited data was developed and used to calculate alternatives for an optimized scheme. 

Compared to the existing distribution solution, cost savings could be proposed that would enable the HIV treatment of 25,000 additional patients per year.

Develop an interactive project map describing regional hydrogen market activities.

Recording of infrastructure requirements based on a questionnaire and individual interviews with partner companies.

Estimation of site-specific hydrogen demand under different ramp-up scenarios, visualization in an interactive heat map for the years 2030, 2035, 2040.

Definition of selection criteria and identification of suitable locations for the development of a sustainable hydrogen filling station infrastructure.

As the cornerstone of the solution, d-fine supported the design of the adaptation of the risk control procedures and the business and IT architecture.

A suitable system was selected, adapted to map market risks and present-value and income-value interest rate risks, and integrated into the IT landscape via a newly developed data warehouse. 

The success factor was the integration of methods and processes into the customer's IT landscape. This was done in close and agile cooperation between business and IT areas, system vendor and d-fine.