DeepDB makes your organisation’s data and knowledge usable by AI agents. Our two core areas: Data Integration for reliable data flows and Knowledge Systems for knowledge in the right context.
AI agents need reliable data and knowledge in context. With Data Integration, we connect your data sources and build dependable data flows. With Knowledge Systems, we make knowledge accessible and usable by people and AI agents. Across industries and within your IT environment.
We turn your requirements into working data and knowledge solutions. From architecture and implementation to operation, we build the foundation for AI agents in your organisation.
We develop data integrations, knowledge systems and the models, software and interfaces they need. This gives AI agents access to the information and functions they need for your specific tasks.
Discuss use caseWe integrate solutions into your IT environment and support their operation through monitoring, maintenance and support. Access rights, data quality and traceable workflows are part of the design.
Discuss use caseProf. Dr. habil. Michael Kaufmann is CTO and Managing Director of DeepDB and Lecturer in Database Systems at Lucerne University of Applied Sciences and Arts (HSLU). Our team combines research expertise with software engineering and operational experience. Together, we put data and knowledge to work.
Data architecture, AI, strategy. Teaching and research at HSLU.
Marketing, Communication, ICT.
Finance, Legal, HR.
Support, Monitoring, Maintenance, Security.
Development, Integration, Testing, Deployment.
Development, Integration, Testing, Deployment.
Open Source & Standards
DeepDB GmbH is the publisher of Property Graph Markdown (PGM) 0.4.0 Public Draft 1, an open, non-commercial specification project for typed relationships with properties in ordinary Markdown.
PGM is not a DeepDB product or an HSLU project. The specification, reference parser, tests, and viewers are developed publicly on GitHub.
Tell us about your plans. Which data needs to become accessible? What knowledge is missing from your workflows? Together, we identify where Data Integration and Knowledge Systems can make the greatest difference.
Answers about Data Integration, Knowledge Systems and our work with AI agents.
Data Integration connects data sources and applications, harmonises data and provides dependable data flows. Knowledge Systems organise information and domain expertise in knowledge bases, knowledge graphs and assistant solutions. They make relationships and sources accessible. Together, these two core areas create the foundation for AI agents.
We build the data and knowledge foundation and develop the necessary interfaces. This helps AI agents find relevant information, use context and integrate into existing workflows. Together, we define which tasks to automate and where people review or approve the results.
We design the architecture around your systems, security requirements and operational needs. This includes integrating existing data sources and applications with controlled access rights. Where needed, we implement solutions on your own infrastructure.
Prof. Dr. habil. Michael Kaufmann is CTO and Managing Director of DeepDB and Lecturer in Database Systems at Lucerne University of Applied Sciences and Arts. His research focuses on databases, big data management and data science. His official HSLU profile is linked in the team section.
We start with a free introductory conversation about your plans. Together, we review your data sources, available knowledge, intended tasks and IT environment. We then develop a concrete approach with a transparent project plan.
