KIDaS
KIDaS
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AI-Powered Data Platform for Social Services

KIDaS connects people seeking help, caseworkers, and social service providers. Specialised AI agents collect offers, identify needs, and match the right services.

Core Features

01 · Web Crawler

Collect data automatically

AI agents will gather, update, and consolidate service data from public sources – fully automated.

02 · Service Sonar

Detect needs and gaps

Designed to analyse public data sources, identify trends and unmet needs, and suggest new social services.

03 · Matching Service

Match precisely

Aims to bring people seeking help and suitable services together through a service configurator.

A consortium of science, practice, and value partners

FAU Erlangen-Nürnberg
Uni Kassel
ANLEI-Service
Dataciders PRODATO
LWV Hessen
BMFTR
Bathildisheim e.V.
Landschaftsverband Rheinland
Landschaftsverband Westfalen-Lippe

Making social services visible and matching them precisely.

Germany spends around 49 billion euros per year on social and disability assistance, yet finding the right offer remains time-consuming. KIDaS aims to consolidate data, automate maintenance tasks, and strengthen coordination.

Data Platform

Structured exchange between funders, providers, and people seeking help.

AI Agents

Web crawler, service sonar, and matching powered by generative AI.

Responsible AI

Transparency, fairness, and value orientation: design principles from Kassel.

Innovation Engine

Incubator for social-tech solutions, scalable beyond pilot regions.

Why KIDaS

Six goals that drive the KIDaS platform

KIDaS combines data-driven service innovation with responsible AI and an open architecture – designed for impact far beyond the pilot regions.

Faster matching

Instead of months of manual research: caseworkers should be able to find suitable offers in minutes.

Transparency & Fairness

Responsible AI by design: every match is explainable and traceable.

Automatic maintenance

AI crawlers will update data continuously – no more outdated service listings.

Scalable architecture

Open, modular, transferable: applicable in health, education, and integration too.

Identifying needs

Service Sonar will identify unmet needs and suggest new services.

Developed in practice

e-Van tours bring the team directly to social institutions on site.

49 Bn € social & disability assistance / year
2 M+ Social assistance recipients (SGB XII)
Impact & Mission

Match precisely. Identify needs early.

People seeking help should no longer wait months. Caseworkers should be relieved. Welfare organisations should identify needs based on data. KIDaS develops three interlocking AI components for this purpose.

  • Automated collection of social offers via AI crawler
  • Service Sonar: trends & service gaps from open data
  • Matching with service configurator for people seeking help
  • Responsible AI: transparency, fairness, acceptance
Research Approach

Responsible AI by Design.

KIDaS combines Action Design Research with Value-Sensitive Design. Technical innovation and ethical principles are given equal weight. Design principles for agentic AI are developed at the University of Kassel (Prof. Jan Marco Leimeister).

Requirements Analysis

Collect needs together with practice partners.

Platform & Crawler

Iteratively develop the AI crawler and data platform.

Service Sonar & Matching

Set up and validate the core services.

Opening Strategy

Establish scaling as an open ecosystem.

Project Roadmap 01.2026 to 12.2028
  1. 2026

    Understanding what's needed

    Direct exchange with social welfare agencies, service providers, and people seeking support: we analyze information and service gaps and review the state of research on generative AI and multi-agent systems.

  2. 2027

    Building the technological foundation

    We build an extensible, privacy-friendly data platform that connects existing systems, along with intelligent components for data management and a strategy for opening the ecosystem to further partners.

  3. 2028

    Intelligent services for practice

    Matching, AI data agents, and the Service Sonar are piloted together with local organizations, including as part of our e-Van Tour. The project concludes with a concept for sustainable operation beyond its end.