Open Federated Learning as a Service

The OpenFLaaS project is developing an AI framework for the automated, decentralized analysis of industrial documents such as tenders, contracts or product sheets in order to digitize knowledge in companies efficiently and yet securely.


OpenFLaaS is the demand of the Present and need of the Future

  • Industries still scared of moving data to cloud for AI enrichment due to the fear of data and IP leakage
  • Manufacturing Industries lacks AI resources like enough data, compute, skilled man power, etc. to build own AI
  • Empower every business by secure and sovereign digital AI technologies

Market perspective and product promise

Companies collect their knowledge, and thus their core corporate assets, in countless documents. With the help of AI, this knowledge can be analyzed in such a way that it can be used to increase efficiency, recognize new connections and thus extract new information, support decision-making, expand service offerings and much more. Given these advantages, it is not surprising that AI-supported document analysis already has a global market volume of over a billion dollars, even though the field is still in its early stages. However, a major obstacle for IDA is currently the dilemma that the computationally intensive analyzes are carried out on cloud computers. Due to data protection reasons and a lack of trust in cloud providers, many companies are currently foregoing the potential of IDA. The openFLaaS project solves this dilemma by enabling companies to use IDA as a Service (aaS), where the data remains within the company. This is made possible by the development of edge AI rooms that are easily connected to Gaia-X-compliant data rooms via plug-and-play. OpenFLaaS offers companies a cloud edge system for intelligent document and text analysis services on edge devices such as industrial systems and machines, computers, smartphones or tablets. When using these services, companies always retain full control over their data. Any IDA-based value-added products and services in Germany and Europe can be developed based on the results of OpenFLaaS. These in turn can be continuously improved with the project solution, both in terms of their generalizability to any area of ​​knowledge and their adaptation or specialization to certain domains. Thanks to innovative algorithms, the CO2 emissions of the analysis processes are minimized because fewer data transactions are necessary between the edge and the cloud. The legal discussion and case law in the area of ​​data use for text and data mining (TDM) is currently still very dynamic. In the project, the legal risks are assessed and the framework conditions are defined under which commercialization of the data products can take place.

  • Challenge and Innovation
    OpenFLaaS relies on decentralization of AI for intelligent document analysis. The analysis of the documents does not take place in a central cloud, but across edge devices. The starting point for this is so-called federated learning. This is distributed machine learning in which only a global AI model is trained in the cloud, but the training data is stored locally, which enables data protection-compliant solutions.

    The innovation of OpenFLaaS is to combine the principles of edge-level federated learning in protected AI spaces with the open standards of Gaia-X. This enables the training of AI models for intelligent document analysis while maintaining data sovereignty. In the project, secure, federated data rooms are developed and implemented in a Gaia-X-compliant cloud edge continuum. Using the example of industrial document types such as contracts, technical CAD drawings, tender specifications, OpenFLaaS develops federated intelligent services that are able to understand and access different text types and layouts such as tables, body text, headings, formulas, images, headers and footers, etc analyze. The software developed in the project is made available as open source.
  • Use Cases
    The project innovation is demonstrated using a prototype for the planning and tendering of industrial plants based on real data. In a second demonstrator, the same principles for AI-assisted analysis of clinical documents on patients will be transferred and implemented on edge devices. Detailed requirements from users regarding technical implementation, data sovereignty and user-friendliness are collected and the prototype applications are validated with experts from the two application fields.
  • Advantages
    OpenFLaaS enables decentralized execution on IDA at the edge level, eliminating the need for enterprises to load data into the cloud. You therefore do not have to fear any leakage of knowledge through data and can ensure compliance with data protection regulations even towards third parties.

    OpenFLaaS creates secure and trustworthy AI spaces for exchanging data, thereby enabling new digital business models and services for an edge-oriented data economy.

    OpenFLaaS enables the realization of a Gaia-X compatible node for industrial document analysis in Germany, thereby promoting the development of AI-based industrial decision support services to optimize productivity.

    OpenFLaaS creates transparency about IDA-based value-added products and services with an open source solution and thus creates trust in automated document analysis.

    OpenFLaaS enables sustainable IDA as less data is transferred to the cloud.

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