What is KIDaS?
KIDaS (AI-powered data platform for social services) is a research project funded by the BMFTR (2026 – 2028) that uses specialised AI agents to improve the matching of social services in Germany.
The Project
Every year, millions of people in Germany receive support through social services – such as social participation, counselling, or addiction treatment. Matching people with the right services depends heavily on time-intensive caseworker research. Existing digital platforms are often sparse, maintenance-heavy, and rarely drive innovation. As a result, available services go unused despite high demand.
KIDaS is developing an AI-powered data platform that brings together people seeking help, caseworkers, and service providers. At its core is an open data ecosystem that makes social services visible and accessible. AI agents collect and update information automatically; analytics tools identify trends and unmet needs early.
The Three AI Components
Collect data automatically
AI agents continuously collect and consolidate service data from public sources without manual maintenance effort.
Identify needs
Analyses public data sources, identifies trends and unmet needs, and suggests new social services.
Match precisely
A service configurator brings people seeking help and suitable services together in a targeted way.
Responsible AI by Design
KIDaS combines Action Design Research (ADR) with Value-Sensitive Design (VSD). Design principles for agentic AI are developed at the University of Kassel in the Information Systems department (Prof. Jan Marco Leimeister).
Every AI decision should be explainable, fair, and acceptable to all stakeholders. This includes transparency about matching results, fairness across all population groups, and the active involvement of users in the design process.
Four partners, one goal
Four consortium partners work iteratively and practice-oriented: FAU Erlangen-Nürnberg and the University of Kassel as scientific partners, and ANLEI-Service GmbH and Dataciders PRODATO as implementation partners.
The consortium is complemented by associated practice partners: LWV Hessen, Bathildisheim e.V., Landschaftsverband Rheinland, and Landschaftsverband Westfalen-Lippe.
During so-called e-Van tours, the project team visits social institutions on site to gather requirements, collect feedback, and build a competence network.
University of Kassel
Value-oriented design of agentic AI, led by Prof. Jan-Marco Leimeister.
FAU Erlangen-Nürnberg
Data-driven innovation of services, led by Prof. Martin Matzner.
ANLEI-Service GmbH
Concept and development of the KIDaS platform.
Dataciders PRODATO
Concept and implementation of the Service Sonar.
Application Potential
Extensible Data Platform
Integrated AI components are intended to significantly reduce manual maintenance effort and match people seeking help precisely with services.
Scientific Methods
Transferable methods for agentic AI, data-driven service innovation, and the sustainable establishment of digital service platforms.
Social-Tech Incubator
Through a targeted opening strategy and incentive system, the platform is positioned as an incubator for social-tech innovations.