AI Agents for intelligent, autonomous tasks

AI agents autonomously perform clearly defined tasks, make decisions, and interact with systems, data, and people. Leverage AI Agents within your organization to automate operational processes, support decision-making, and implement intelligent workflows — from individual agents to complex multi-agent systems.

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Automation through AI Agents

Operational AI Agents in Agentic Systems

Organizations are increasingly challenged to efficiently automate operational tasks, decisions, and workflows while processes become more dynamic and less predictable. Traditional automation quickly reaches its limits in such environments. AI Agents offer a pragmatic solution by autonomously executing clearly defined tasks, processing information from various systems, and acting contextually based on the situation.

statworx supports your organization in the development and implementation of powerful AI Agents that integrate seamlessly into existing processes and IT landscapes. From technical design and prototyping to evaluation and productive deployment, we guide you in establishing AI Agents strategically and securely within your organization.

Definition

What are AI Agents?

AI Agents are software-based systems that autonomously execute tasks by processing information, making decisions, and taking targeted actions. Unlike traditional automation solutions or simple chatbots, they are not limited to predefined workflows or isolated responses. Instead, they pursue specific goals, continuously process new information, and dynamically adapt their behavior to the respective context.

For example, an agent may retrieve data from multiple sources, interpret it, derive decisions, and subsequently execute actions within connected systems. Depending on the use case, AI Agents can operate individually or as part of a multi-agent system, where several agents collaborate and coordinate tasks collectively. In this way, AI Agents form the operational foundation for flexible automation scenarios.

Typical characteristics of AI Agents:

Autonomous execution of clearly defined tasks
Processing contextual information from various systems
Interaction with APIs, tools, databases, and applications Context-dependent decision-making
Collaboration between multiple agents within multi-agent environments

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Our Services

Our AI Agent offerings

To ensure that AI agents create sustainable business value, organizations require an end-to-end value chain. We support you throughout the entire process — from initial prototypes and iterative refinement to robust, production-ready solutions for concrete use cases. In addition, we empower your teams through targeted enablement programs focused on agentic AI to ensure long-term success.

Strategy

Agentic AI Use Case
Workshop

In a collaborative workshop, we analyze your existing processes and identify suitable application opportunities for Agentic AI. The focus lies on a structured capability assessment, reliable ROI estimation, and the prioritization of potential implementations.

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Agentic AI Impact Assessment

We evaluate the efficiency potential, business value, and feasibility of agentic AI systems within your organization. The goal is to transparently assess opportunities and risks while realistically identifying the full potential of the technology.

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RPA-to-Agent Migration Strategy

Through a structured RPA-to-Agent migration strategy, we assess existing automations, analyze associated risks, and develop a robust transition roadmap toward Agentic Process Automation.

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Trainings

Agentic AI for Leaders Training

Executive-focused program combining strategic insights and practical demonstrations of AI Agent capabilities. Leaders learn to identify opportunities, assess risks, and develop strategies.

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Hands-on AI Agents Development Training

Intensive technical training where participants build and deploy AI Agents using industry-standard tools. Covers agent architecture, programming patterns, and integration of best practices.

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Agentic AI Software Engineering Training

Practical workshop instructing developers on how to speed up their coding process using AI agents. Includes automated code generation, test automation, and intelligent code review.

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Solutions

Agentic AI Prototype

Leverages historical and external data to develop autonomous negotiation strategies with suppliers. Integrate the agent into your procurement systems or automate the process via email.

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AI Negotiation Agent

Leverages historical and external data to develop autonomous negotiation strategies with suppliers. Integrate the agent into your procurement systems or automate the process via email.

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Data Intelligence Assistant

An agent interface for data-driven decisions. Type in a request and the assistant retrieves the internal information you need and transforms it into actionable insights.

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Benefits of AI Agents for your business

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Greater efficiency

AI Agents automate clearly defined tasks while reducing manual effort and minimizing errors.

Increased flexibility

Agents dynamically respond to new information and adapt their behavior contextually.

Scalability

AI agents can be expanded incrementally and integrated into additional processes and systems over time.

Reduced workload for teams

Employees can focus on strategic and value-generating activities while AI agents handle operational routine tasks.

Our strength

statworx is one of the leading Consulting and Development Companies for Data & AI in the German-speaking region.

Our ecosystem enables a holistic view of Data & AI.

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We focus intensively on the interfaces between people, economy, society, environment, and AI technology.

Sebastian Heinz

Founder and CEO statworx

Our spotlight topics at a glance:

Agentic AI

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AI Act Compliance Solution

CustomGPT Chatbot

AI Strategy Whitepaper

Generative AI

Customer Service Automation

Tools, Partner & Technology

15+

years of experience in Data Science, ML, and AI

100+

clients from 10 industries and growing

85+

experts from more than 17 fields of study

1,000+

successfully implemented Data and AI projects

Process optimization

How AI agents can be applied in practice

In practice, AI agents are deployed in various forms. Individual agents handle specific tasks such as data retrieval, decision support, or individual process steps. In more advanced scenarios, multiple agents collaborate and coordinate activities within multi-agent systems, enabling the automation of complex end-to-end process chains.

A critical success factor is seamless integration into existing IT landscapes, combined with clearly defined responsibilities, control mechanisms, and interfaces. statworx acts as your experienced partner in guiding AI agents from initial prototypes into productive enterprise deployment and ensuring their long-term operation and optimization.

Use Cases for AI Agents

Intelligent Contract Analysis

AI Agents continuously monitor, analyze, and extract insights from thousands of contracts, automatically flagging risks, opportunities, and renewal requirements while ensuring compliance across global operations.

Autonomous Customer Service

An agent system manages complex customer inquiries across channels, automatically routing, escalating, and resolving issues while learning from interactions to improve service quality and reduce resolution time.

Financial Anomaly

AI Agents continuously monitor financial transactions across subsidiaries, detecting fraud patterns, compliance violations, and accounting irregularities before they impact business operations, preventing potential losses.

Sales Intelligence

AI Agents analyze customer interactions, market trends, and competitor moves to automatically generate personalized sales strategies and recommend next best actions for each opportunity.

Code Development

An agent system assists development teams by generating code, conducting reviews, identifying security vulnerabilities, and suggesting optimizations, dramatically accelerating software delivery cycles.

Knowledge Base Evolution

AI Agents automatically maintain and update corporate knowledge bases, identifying outdated information, generating updates, and ensuring consistency across documentation while preserving institutional knowledge.

Regulatorische Compliance

AI Agents monitor regulatory changes across jurisdictions, automatically updating compliance documentation, flagging required changes, and orchestrating implementation of new requirements across the organization.

SEO Strategie

AI Agents analyze website content, keywords, backlinks, and competitor strategies to optimize search engine rankings. This provides actionable insights for content improvements, keyword targeting, and link-building opportunities.

Automatisierte Recherche

An AI Agent continuously scans scientific papers, patents, and market research to identify relevant insights, reducing research time by 85% while increasing the discovery of valuable opportunities.

Request a project now with no obligation

Non-binding initial consultation

Free situation and requirements analysis

Response within 24 hours

Start your AI Agent journey the right way

Free consultation

Discuss your challenges and goals in the area of Data & AI with us.

Tailored offer

Receive a customized and transparent offer.

Presentation & contract award

We present our approach to all relevant stakeholders.

Onboarding with project team

Our dedicated project team takes care of your needs.

Create value from Data & AI

Non-binding initial consultation

Free situation and requirements analysis

Response within 24 hours

Marcel Plaschke

Head of Strategy, Sales & Marketing

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AI Agents: FAQ

What are AI agents and what are they used for?

AI agents are software-based systems capable of autonomously executing clearly defined tasks. They process information from multiple systems, make decisions, and automatically perform actions. Organizations use them for process support, decision assistance, operational automation, and the coordination of more complex workflows.

What is the difference between AI agents and agentic AI?

AI Agents are individual autonomous software entities that independently execute tasks, process information, and trigger actions.

Agentic AI, on the other hand, refers to the overarching concept in which multiple AI agents are coordinated to pursue shared goals and manage complex, dynamic workflows.

How do AI agents differ from traditional automation solutions or chatbots?

Unlike rule-based automation systems or simple chatbots, AI agents are not restricted to rigid workflows or isolated responses. They operate goal-oriented, respond dynamically to new information, and adapt their behavior contextually. This makes them particularly suitable for processes involving exceptions, changing requirements, or high decision complexity.

Do AI agents always need to be part of a larger agentic AI system?

No. AI agents can operate independently for clearly defined tasks or as part of a broader agentic system. In more advanced scenarios, multiple agents collaborate within so-called multi-agent systems. The strategic orchestration of such systems is often addressed within broader agentic AI initiatives.

What prerequisites does my company need for implementing AI agents?

In general, organizations require a suitable IT infrastructure as well as access to relevant data and business applications. However, companies do not need to be perfectly prepared from the outset: we support you from initial technical design and prototyping to the integration of AI agents into existing systems and processes.

How does statworx support companies in introducing AI agents?

statworx supports organizations throughout the entire journey — from team enablement and training to prototyping and the development of production-ready AI agents. In addition, we assist with integration into existing IT landscapes, transition into productive operations, and the long-term evolution of AI agent solutions.