Division Supply Chain Services at Fraunhofer IIS
Division Supply Chain Services at Fraunhofer IIS

AI-enabled Insight & Foresight

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With our AI-supported methods, we can quickly and validly identify insights and trends from large, constantly growing volumes of unstructured text data. To do this, we use methods developed in-house that allow us to process a wide variety of data sources such as patents, publications, homepages, company data or user contributions continuously and across languages. We make the results available in customized applications and dashboard formats or provide support in implementing them in your own system or process landscape.
 

To examine entire industries and domains, we combine dynamic knowledge modeling tools (semantic web) with AI-guided data analysis methods in a holistic process that automatically creates the empirical basis for expert opinions, trend determinations and scenario considerations from a variety of unstructured market and industry data.

Our expertise

Our expertise Your challenges
  • Automated, AI-supported processing and analysis of structured and unstructured text data using natural language processing
  • Rapid development of AI prototypes for feasibility studies and proof of concept.
  • Development of domain-specific ontologies and dynamic modeling of knowledge in knowledge graphs / knowledge graphs
  • Transfer of results into established methods and tools of innovation management and market research
  • Analysis and transferability of concepts such as agents, reasoning, RAG systems to operational issues
  • High, international innovation dynamics: Technological development is progressing: patent applications are increasing globally, R&D development activities are taking place in a wide variety of countries. But how can technological progress be monitored across language barriers? How can changes be recognized at an early stage and appropriate decisions derived?
  • Manually unmanageable amounts of data: Global data volumes are also continuing to increase. The number of patents and publications is constantly increasing, as is the number of user contributions, customer reviews, blog posts, internal company knowledge sources and much more. This information can no longer be collected or processed efficiently by individual employees.
  • Rapid AI evolution: The capabilities of AI methods and models are developing rapidly. The well-known ChatBot ChatGPT was only presented to the public at the end of 2022, and since then has led to a creative explosion of methods and further developments based on it. AI-based tools and applications are also subject to short-lived cycles. How can these many new technological concepts and models be transferred to operational use cases - quickly and in a results-oriented way?

Referenzen

Organization

Department »Innovation and Transformation«

The department develops management-oriented models and data-based processes for the design of data-driven and sustainable organizations. We act as trend scouts and idea generators, analyze AI-supported market and technology trends and provide recommendations for circular innovations. Taking into account the perspectives of users and organizational ecosystems, we promote digital and sustainable transformation in manufacturing companies, the energy industry, retail and the healthcare sector.

To the department