What is an autonomous AI agent?

An autonomous AI agent plans, decides and executes tasks independently - without dedicated prompts. It uses tools, accesses data, remembers contexts and adapts dynamically. These capabilities make it possible to take on complex processes that go far beyond simple chatbots.

What can AI do in controlling?

AI in controlling recognizes patterns in large amounts of data, creates forecasts, automates reports and detects anomalies. In this way, it provides a sound basis for decision-making, saves time and increases accuracy - especially when it comes to forecasts, scenario analyses and budget deviations.

Are AI agents the future?

AI agents are seen as a central component of the next wave of digitalization. They combine generative AI with automation, tool use and the ability to learn - enabling productive, interactive systems that control processes independently and bring real efficiency gains.

A prompt is an explicit prompt that is used to control classic language models. Autonomous AI agents work differently: they plan their next steps themselves - without needing a prompt for each step.

Which tools do AI agents use?

Which tools AI agents use depends heavily on the use case. For example, AI agents can access internal systems, control APIs, interact with databases or use external services such as calendars, email clients or Jira. The important thing is that they can use these tools independently and depending on the context.

A humanoid robot works at a computer in a modern office, with blurred people in the background.

AI agents

Lean, smart and made for your company

AI agents from MaibornWolff - the perfect fit for your business

Would you like to automate your business processes and increase customer satisfaction in the process? Then we will work with you to develop AI agents that are precisely tailored to your processes - without unnecessary technological ballast, but with maximum added value for your business.

MaibornWolff accompanies you through all phases with an interdisciplinary team of experts: from a clear strategy and technical development to seamless integration into your existing systems. Always customized, efficient and geared towards your goals - in line with our guiding principle: Less Technology. Better Business.

Arrange a free consultation appointment

Customized AI agents - because standard is not always enough

Our AI specialists combine expertise from three worlds: Artificial intelligence, cloud technologies and software development. This results in solutions that are not only technically impressive, but also prove themselves in practice: robust, scalable and future-proof.

Intelligence that fits

Our agents are tailored to your processes. They meet the highest standards of data protection, scalability and interoperability - and deliver reliable performance day after day, without breaks or after-hours.

Seamless integration

We integrate your AI agents directly into existing systems. Your workflows continue to run as usual, only faster, smarter and less stressful. And without having to rebuild familiar processes.

Measurable efficiency

We make success visible: KPIs show where you can save time, costs and nerves and still retain your customers for your brand. Our AI agents achieve different levels of autonomy - tailored to your needs.

Future-proof technology

We rely on scalable architectures and modern, interchangeable language models. This ensures that our AI agents remain fit even as requirements grow: today, tomorrow and the day after tomorrow. As reliable as on day one.

Conversational & Autonomous Agents

We develop agents that communicate and act independently. Whether chatbot, voice assistant or complex system agent: our solutions think for themselves, interact in a context-sensitive manner and access external tools and data as required.

Agentic Automation

Decision support through AI agents

Technological foundations for our AI agents

We use a reference architecture we have developed for AI agents, which consists of three central components, among other things. Your customized AI agents are created on this basis.

Language model: serves as a decision center. Modern language models enable logical conclusions, planning of complex tasks and processing of multimodal input (text, images, etc.). We use appropriate language models for the task at hand.
Orchestration layer: coordinates processes, manages states and resources. This layer controls the behavior of the agents using a framework tailored to your use case.
Tools: enable access to databases, documents or other data sources so that the AI agents can go beyond their basic language model capabilities.

Successful AI projects from our practice

Every company has its own challenges - and this is precisely where our strength lies. We do not develop off-the-shelf solutions, but design each AI project according to the individual goals and framework conditions. Our AI projects show how ideas become concrete results.

To all references

Research: AI-supported robotics for employees with physical limitations

With demographic change, employees with physical limitations need better support to remain productive. Assistance robots can help, but are not flexible enough. The KiRo4LeMi research project aims to use AI to dynamically adapt robots to individual changes in performance. Using digital models and "living personas", the AI optimizes robot operation in real time.
See robotics reference

Research: AI-supported robotics for employees with physical limitations

3 years

research project, funded by the Bavarian Ministry of Economic Affairs

Design of the robot

more individuality thanks to AI

Digital twin

helps to be able to react quickly during operation

See robotics reference
Siemens: AI demand prediction platform for industrial production planning

Siemens is looking to the future with the AI Demand Prediction Platform. Thanks to machine learning and AutoML, precise demand forecasts can be created for over 100 products and production can be better planned. Launched as a proof of concept, the platform quickly developed into a system that can be used productively. The self-service web application will soon be used in other plants.
See Siemens reference

Siemens: AI demand prediction platform for industrial production planning

Project duration

Since February 2022

Proof of concept

in a few weeks

Time series prediction

for 100 different products

See Siemens reference
TÜV NORD GPT: Development of AI assistance

Find relevant information faster by chatting with documents? It's possible! The TÜV NORD GROUP uses GPT technology in the secure Microsoft Azure Cloud. With the aim of optimizing knowledge management and efficiency. The system enables new usage options within the testing group and is operated securely. Find out more about the innovative AI assistance system now.
See TÜV NORD reference

TÜV NORD GPT: Development of AI assistance

Project duration

since September 2023

33.000

GPT applications in the first month

ChatGPT Model 4

in the European Microsoft Azure Cloud

See TÜV NORD reference
digikoo: A data platform for the Azure Cloud

Structured geodata, automated quality assurance, seamless provision - we developed a powerful Snowflake data platform on Azure for Digikoo. It makes analysis easier for data scientists and lays the foundation for precise forecasts and new use cases.
See digikoo reference

digikoo: A data platform for the Azure Cloud

5 months

Project duration

Climate change

Plan digitally and implement efficiently

Foundation data platform

Microsoft Azure Cloud

See digikoo reference
Bayernwerk: Knowledge management via teams

Experience must not be lost - Bayernwerk digitizes the knowledge of long-standing employees. MaibornWolff designed an intuitive MS Teams app with a clear UX/UI. Close collaboration, lived Scrum values and user-centered development make the app a success. Promoting exchange, optimizing processes - this is how knowledge transfer works today.
Read more

Bayernwerk: Knowledge management via teams

6 months

Project duration

Target:

Identify implicit knowledge

Requirements:

a user-centered, intuitive and clear UX/UI design

Read more

Typical challenges when introducing AI agents

AI agents have enormous potential - but in practice, similar obstacles keep cropping up. Companies are often faced with unclear objectives, have to deal with scattered data sources or must first build up the necessary understanding of AI internally. Regulatory requirements, non-scalable data architectures, unknown entry costs or the general question of how to get started also slow down many initiatives.

To ensure that innovative ideas do not fail in the face of reality, we support you wherever you need us: from the initial idea to the productive use of your agents.

Distribution

AI agents take over the pre-qualification of leads, automate quotation processes and prepare decisions based on data. This leaves your team more time for what no agent can replace: real customer relationships.

Customer support

Accounting & Administration

IT & Service Management

Manufacturing & Maintenance

Purchasing & Supply Chain

Management & Strategy

Current guides on the topic of artificial intelligence

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FAQ: Frequently asked questions about AI agents

What is an autonomous AI agent?

An autonomous AI agent plans, decides and executes tasks independently - without dedicated prompts. It uses tools, accesses data, remembers contexts and adapts dynamically. These capabilities make it possible to take on complex processes that go far beyond simple chatbots.
What can AI do in controlling?

AI in controlling recognizes patterns in large amounts of data, creates forecasts, automates reports and detects anomalies. In this way, it provides a sound basis for decision-making, saves time and increases accuracy - especially when it comes to forecasts, scenario analyses and budget deviations.
Are AI agents the future?

AI agents are seen as a central component of the next wave of digitalization. They combine generative AI with automation, tool use and the ability to learn - enabling productive, interactive systems that control processes independently and bring real efficiency gains.
What is a prompt?

A prompt is an explicit prompt that is used to control classic language models. Autonomous AI agents work differently: they plan their next steps themselves - without needing a prompt for each step.
Which tools do AI agents use?

Which tools AI agents use depends heavily on the use case. For example, AI agents can access internal systems, control APIs, interact with databases or use external services such as calendars, email clients or Jira. The important thing is that they can use these tools independently and depending on the context.