Generative AI and LLMs in practice
Generative AI (GenAI) and large language models (LLMs) are far more than just trends – they are revolutionizing business processes through automation, enabling personalized customer experiences, supporting data-driven decision-making, and accelerating development processes. At the same time, they enhance human creativity and boost efficiency across a wide range of applications. fortiss actively advances these technologies, shaping their ongoing development in terms of reliability, usability, and compliance – for science, industry, and society.
In close collaboration with industry partners, fortiss develops practical solutions that enhance decision-making and optimize workflows. Our focus areas include Natural Language Processing (NLP), knowledge graphs, and edge-cloud orchestration. Through seamless integration into existing software systems, we enable scalable, secure architectures that meet the highest quality standards – while simultaneously reducing unpredictable system behavior.
Research focus
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fortiss integrates large language models (LLMs) into software and systems development to optimize development processes and modeling. This approach enables the automated generation of modeling artifacts from natural language, the transformation of requirements into functional architectures, and the enhancement of workflow efficiency.
Furthermore, fortiss applies generative artificial intelligence (GenAI) in software development to improve software quality through code generation and analysis techniques. In the field of automotive engineering, GenAI is used to generate image data for validation tests of autonomous vehicles.
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Our scientists develop advanced technologies to optimize the quality of LLM outputs. This includes improving text normalization, enhancing output quality, and automating evaluation. Methods such as LLM2Vec for data organization and the "LLM-as-a-judge" concept enable more precise analysis and optimization of input data and processes.
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To ensure the security and compliance of LLM applications, fortiss implements an advanced monitoring framework. This framework enables the enforcement of custom security and compliance policies, detection of hallucinations, privacy measures, and filtering mechanisms to avoid inappropriate content, ensuring the integrity and trustworthiness of AI applications.
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In the field of industrial applications and edge computing, fortiss explores the use of LLMs to optimize automation and efficiency processes. The integration of LLMs into edge-cloud architectures enables the realization of energy-efficient processes, optimized production workflows, and intelligent automation across various industries.
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fortiss investigates the application of LLMs to support neurodiverse individuals – particularly those with Asperger’s Syndrome or ADHD – in professional communication and social interaction. The focus is on developing solutions for communication facilitation, assistive applications, and AI-powered tools to promote accessibility and inclusion in the workplace.
Scalable and practical solutions for SMEs
Beyond general research on generative AI, fortiss develops specialized LLM-based solutions to provide small and medium-sized enterprises (SMEs) with a technologically sound and economically viable way to access Artificial Intelligence (AI). This is not only about providing practical AI solutions but also about their targeted adaptation to industry-specific requirements in order to systematically harness innovation potential.
A key research focus is the precise adaptation of LLMs for automating business processes, optimizing decision-making, and improving efficiency. Particularly in sectors such as manufacturing, logistics, and services, fortiss explores the use of LLMs to optimize supply chains, predictive maintenance strategies, and intelligent communication systems.
By developing systems that are easy to configure and use, fortiss lays the foundation for a sustainable and cost-effective integration of LLMs into SMEs. This enables not only cost-effective implementation but also a long-term increase in competitiveness through adaptive and future-proof AI infrastructures.
LLM-based process optimization
LLMs for automating business processes – from content creation to document processing – and for reducing operational costs.
Synthetic test data generation through LLMs
LLMs generate synthetic test data for AI validation. fortiss provides SMEs with technologies for independent, cost-efficient testing of perception systems, thereby lowering the barriers to entry for AI.
LLM-centered regulatory compliance by design
Agentic approaches to assist the extraction of regulatory requirements from norms and standards and to effectively manage changes throughout the software development life cycle.
Similarity analysis using LLMs
Identifying commonalities in content between texts for applications in product search, data integration, or knowledge management.
LLM-based structuring of technical requirements
Converting technical and domain-specific requirements into machine-readable formats to serve as the basis for automated development, analysis, and documentation processes.
LLM deployment on edge devices
Optimizing LLMs for low computing power and low energy consumption — particularly for SMEs — to enable resource-efficient and high-performance usage.
Reference projects
Accelerated innovation processes through an AI-supported ideation process
Measuring the success of generative AI in the software development life cycle
Automation of vehicle electrical systems through AI and multi-agent systems
Intelligent error analysis for SAP planning processes using generative AI
GraphRAG-based training and education system for robot-assisted medical procedures
Agentic AI for modernizing the government
Modular agent-based AI framework for an effective public administration
AI-based text evaluation for automated processing of customer inquiries
Services & insights
Your innovation starts with fortiss
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