Our services for all industries: From AI to sustainability

Our training program for specialists and managers offers a diverse selection of practical AI courses: compact introductory courses, industry- and subject-specific training, certification courses and tailored in-house training for companies.

Are you a manager or innovation driver with limited time? Our AI briefings provide you with comprehensive knowledge on the potential, possible risks and technical foundations as well as practical applications of AI in your company. Get a compact and well-founded overview of the latest developments in the field of AI, such as generative AI.

In a hackathon lasting several days, we work with you to develop innovative application possibilities using the latest AI technologies, e.g. generative AI. With your interdisciplinary team and based on your company data, we develop an initial proof of concept that makes the practical benefits of the technology directly tangible and highlights the potential and risks. AI Innovation Campus means experiencing hands-on in a team what is possible and bringing initial solutions into the company.

During shadowing, our scientists accompany your specialists in their day-to-day work in order to identify potential AI use cases. Through direct observation, we gain valuable insights into your processes and evaluate the use cases in your natural working environment.

We analyze your processes and data to identify relevant AI use cases and check their feasibility. After evaluating and prioritizing the use cases, we create a roadmap and implementation strategy for the realization of your projects.

In our use case workshops, we work with you to identify and evaluate potential applications of AI in your company in a structured manner. We take your individual requirements into account (e.g. in terms of trustworthiness or technical aspects), assess the potential and feasibility of the use cases, prioritize them and outline the next steps for implementation.

The successful use of AI in an organization requires not only a pioneering spirit, but also strategic and technical foresight. As independent consultants, we support you in all technical issues relating to artificial intelligence: from the selection and fine-tuning of suitable models for your specific use case, to implementation (on premise or in the cloud) and seamless integration into your existing systems - always with your overall strategy in mind.

Digitalization and IT Strategy

We develop strategies, concepts and management systems for the digitalization of companies, authorities and public stakeholders and implement them with you. Would you like to combine digital and sustainable transformation? We would also be happy to support you with your »twin transition«. 

Sustainability

Develop your sustainability strategy with us and implement it with us. To do this, we work with you to analyze how you are positioned in terms of sustainability and support you with your goals and the development of corresponding key performance indicator models.

Experimentation Platform

We test, evaluate and benchmark different AI models and identify the best approach for your use cases. In a holistic analysis, we take into account various aspects such as resource efficiency, performance, data usage and trustworthiness, depending on the use case and requirements. If necessary, we can set up a dedicated testing platform for you.
 

Operating Platform

We provide you with a secure and trustworthy complete solution for the productive operation of your company-specific applications, both on-premise and in the private cloud. We use open source models and components - open to all providers and future-proof. If required, we provide support with integration, operation and further development.

Large, multimodal language models integrate various data formats such as text, images, audio or video in order to understand them and, in particular, to generate natural language. We use this technology, for example, to develop assistance systems for administration, create medical documents, analyze large media archives or optimize financial processes. To do this, we use existing, pre-trained models or adapt them to specific tasks or domains (finetuning).

Using Retrieval Augmented Generation (RAG), we can also integrate your company's internal knowledge in a fact-based manner and support you with targeted prompting (e.g. prompt design, zero-shot prompting).

In Addition, Teuken provides companies and institutions with a trustworthy language model that we co-developed, which is proficient in the 24 official European languages and can be adapted to your own corporate purposes.

Our technologies for spoken language include:

• systems for automatic speech recognition
• speech synthesis
• speaker recognition
• voice-controlled interaction

The systems are used by companies to automate processes in spoken language, make information more efficiently accessible and enable barrier-free communication - for example through live subtitling, audio analysis in (media) archives or intelligent voice assistance systems in customer service, medicine or industry.

AI agents can carry out complex jobs with a series of actions largely autonomously, taking automation in companies to a new level.

Agentic AI and modern AI agents use generative AI and draw on a pool of different models to understand their environment multimodally, develop and dynamically adapt plans and coordinate their actions with the client. We use AI agents, for example, for risk assessment in the compliance area of companies, for workflow automation in approval processes in the legal sector or for controlling robots and systems in industrial environments. The resulting benefits for you range from process optimization, increased efficiency and flexibility to personalization and cost savings.

AI add-ins bring intelligent functions directly into your existing work environments such as Word or Excel. They supplement the familiar software with adaptive support, e.g. through AI-based automatic text suggestions, automated audit notes or assistance functions - without having to switch systems. AI add-ins thus enable low-threshold AI use that can be flexibly adapted to individual processes - without costly system migrations or lengthy user training.

In finance, for instance, financial reports in Word can be checked for completeness and consistency according to previously defined criteria, e.g. prescribed paragraphs and internal company specifications.

Utilize the potential of structured and unstructured voice and text data. Using state-of-the-art NLU methods, we develop customized solutions that provide you with precise insights and a sound basis for decision-making. From Named Entity Recognition to automated document classification - optimize your document-based business processes with AI and increase the efficiency of your information processing.

We use specialized encoder models that are specifically tailored to the respective use case, for example in the healthcare or public sector, and provide these solutions on-premise or in the cloud.

Scenario-based simulation is used to realistically simulate alternative processes or decision-making situations with the help of AI. For example, a combination of language models and classic machine learning methods can be used to simulate portfolio simulations in finance or different initial constellations in court proceedings. Different initial situations, influencing factors or variants are systematically taken into account in order to better understand the effects, understand the interactions of different parameters and thus make well-founded decisions. Risks are identified at an early stage, processes are made more resilient and decisions are made with foresight.

Recommender systems make context-related suggestions based on data patterns, experiential knowledge and previous user behavior. Our systems suggest relevant content, next steps or decision options.

We use them, for example, for audit processes in finance or law and customize them individually. Recommender systems are used in particular when structured tasks need to be supplemented with experiential knowledge, checklists or analysis steps need to be flexibly expanded or standard procedures need to be individualized.

We develop systems that enable machines to see and understand. With our expertise in classic image processing and deep learning, we create solutions that not only capture visual information, but also analyze it intelligently.

Our technologies are used wherever precision and speed are required: in automated quality control, object recognition or safety-critical applications. Thanks to modular architectures, scalable infrastructure - from edge to cloud - and a high degree of adaptability to real production conditions, our systems can be efficiently integrated and flexibly expanded.

Our AI-supported forecasting methods support suppliers, manufacturers, retailers and wholesalers in making well-founded predictions - for sales, stock levels, returns or transport flows, for example. Complex developments or uncertainties such as fluctuations, trends and bottlenecks can be identified at an early stage, even with incomplete data. Based on this, we optimize orders, goods distribution and returns in real time. This makes your entire supply chain more efficient, more flexible and easier to plan.

Many processes in the value chain of companies, especially in retail, consist of sequential steps in which earlier decisions influence later ones. With sequential decision making, we continuously analyze the status of the entire process and develop new, situation-appropriate courses of action for the individual process steps. Adaptive, intelligent systems are created on this basis. One practical example is the use of AI agents in supply chain logistics. An AI agent monitors the status of deliveries, detects disruptions at an early stage and dynamically adjusts routes or delivery schedules - for smooth and punctual processes.

We enable the future-proof integration of your AI solutions into productive operations. Based on our MLOps strategies (use of tailor-made processes, suitable tools and established technologies), we optimize the entire life cycle of your machine learning projects - from development and deployment to continuous monitoring and ongoing improvement of AI models and applications. Automated workflows and scalable processes guarantee the sustainable and smooth deployment of your AI solutions in the company.

We support you in identifying and technically interpreting the regulatory requirements for your AI system. We also give you an overview of which AI standards and norms apply to your AI system. This not only ensures that your system is developed in compliance with the law, but also lays the foundation for sustainable quality assurance.

We support you in setting up efficient and effective AI governance. This ensures that you consistently implement regulatory requirements (e.g. from the EU AI Act) and that your AI systems meet the required quality standards.

An important building block for this is our Trustworthy AI Operations (TAIOps) framework, which extends Machine Learning Operations (MLOps) in such a way that applicable requirements for AI trustworthiness are automatically taken into account.

We safeguard your AI systems by intelligently combining different methods to create robustness and transparency as well as uncertainty assessment of neural network outputs. In this way, we reduce AI-specific risks and enable a higher degree of autonomy for your AI systems during operation.

We access the quality of your AI system using the AI assessment catalog developed by us as well as relevant norms, standards and laws. To do this, we define the assessment object as well as the targets of the assessment and determine the depth of the assessment.

You receive the results of the assessment in the form of a scientific report.

Assessment criteria form the basis for objectively evaluating the quality of AI systems. We develop AI assessment criteria that are adapted to your domain and provide support with validation in pilot assessments. We can draw on our tried-and-tested AI assessment catalog, which we have already used to successfully carry out a large number of AI assessments.

The systematic testing of AI systems is an essential part of AI development and assessment. We provide you with tailor-made tools for testing your AI systems, e.g. specific benchmarks for assessing the quality of large language models (LLMs).

The systematic testing of AI systems and the development of new business models for third-party assessment of AI systems require a high degree of automation of AI assessment workflows.

To this end, we have developed tailor-made multi-party MLOps environments that can be accessed by different parties such as developers or testing organizations. These enable audit-proof assessment workflows with a high degree of automation and the integration of different assessment tools.

We analyze your requirements and pay attention to resource-saving training and resource-efficient operation while ensuring the required performance. If required, we focus on small, locally operable AI models, for example. Alternatively, we can compress large AI models or develop resource-saving AI models for your company. For example, the large language model Teuken, which we co-developed, has a new type of tokenizer that makes the training and operating of the model more efficient.

Do you work in an environment that often requires complex calculations or analyses, e.g. in materials science or drug development, finance, logistics or IT security? Take advantage of the potential of quantum technologies today, especially quantum machine learning, and check whether your mathematical challenges can be solved more resource-efficiently than before with Quantum Computing (Quantum Machine Learning) and our Evo Annealer.

We support cities, companies and the society with methods for analyzing climate change risks and adaptation planning. To this end, we offer comprehensive climate risk assessments and resilience analyses for specific adaptation and protection measures. We also develop individual strategies to increase resilience and support their implementation in decision support systems.