Agentic AI

Diverse Applications for business Success

From Language Models to Autonomous AI Agents: In recent years, AI has taken a giant leap forward. What started as general-purpose language models has evolved into autonomous AI agents – systems that can independently pursue goals, make decisions, and complete tasks. By combining conversational skills, decision-making capabilities, and the use of digital tools, these agents can achieve far more than traditional AI applications.

The implementation of agentic AI is as unique as the challenges it addresses. Here are a few examples:

Customer Advisory
Agentic Voice AI can hold personalized 1:1 conversations, provide tailored product recommendations, and prepare the purchase decision.
Product Development
By combining customer feedback, market trends, and technical data, agentic AI can propose innovative features and product ideas.
Quality Control
Error data can be analyzed to detect patterns and proactively suggest measures for preventing future issues.

OUR SERVICES

Agentic AI Consulting

Every implementation is as unique as the challenge behind it. Whether it's process automation, decision support, or autonomous interaction – our agentic AI systems aren't just integrated, they're developed with you. Built on your infrastructure, aligned with your goals, and tailored to the specific demands of your industry.

Agentic AI in E-Commerce

Diconium’s agentic AI solution takes on the role of a personal product advisor in online shops – guiding customers through their journey and preparing them for purchase decisions.

Agentic AI in the Automotive Industry

Agentic AI is redefining the driving experience—turning the vehicle into an intelligent, personalized, and conversational companion. The vision is more than just voice control, it’s a proactive co-pilot that understands the driver’s needs, adapts to preferences, and acts autonomously.

Your benefits with us

Our multidisciplinary team of more than 200 data and AI experts is your implementation partner for customized use cases in the field of artificial intelligence and generative AI focusing always on AI quality, safety and security.

Business meets Tech

AI is not just about innovation-it must align with your company’s requirements, IT infrastructure, and legal framework. Our cross-functional teams deliver solutions that work in practice and comply with regulations.

From idea to implementation

A concept on a slide deck is just the beginning. Our Product Owners bridge the gap between strategy and execution, transforming your vision into a functional AI product through precise and forward-thinking requirements management.

Outcome over output

Success isn’t measured by dashboards alone. Our AI engineers rigorously test models, while our process designers ensure seamless integration into your business workflows. Our goal: AI solutions that deliver real, measurable impact.

Legal guidance from day one

Our Legal Engineers are involved from the very start to ensure compliance with the EU AI Act and data protection regulations. The result: sustainable implementation and user trust built from day one.

Let’s talk about Agentic AI in your organization!

At Diconium, we know that every AI journey is unique. That’s why we meet you exactly where you are-whether you're building the organizational foundations, identifying value-creating use cases, or scaling AI across your entire company.

The question is not if agentic AI can create value, but where. Which application field can you imagine for your company?

Get in touch with us.

Jürgen Wohler

director business development

+49 1522 4971815

contact@diconium.com

FAQ

What is Agentic AI and how does Agentic AI differ from “classic” AI?

Agentic AI refers to a new generation of AI systems that don’t just respond to requests-they act autonomously, make decisions, and carry out complex tasks over extended periods. These systems are not merely reactive, but proactive and goal-driven-digital agents with the freedom to take action.

A traditional AI model might answer a question or generate text. An agentic AI system, on the other hand, can independently conduct research, analyze data, create a presentation, and even send it via email-all based on a higher-level objective.

Learn more in our blog post.

How does Agentic AI work?

Agentic AI systems pursue goals and act autonomously. Each agent has a clearly defined role and leverages knowledge from databases, tools, or APIs. Decisions are made based on natural language input, allowing agents to respond intelligently and contextually.

Through an orchestrator, each agent stays synchronized with others—ensuring seamless collaboration across the system. The result? Interactions that feel remarkably human.

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How are context, memory, and feedback processed in agentic AI?

In agentic AI systems, context, memory, and feedback play a central role. They enable agents to act purposefully, adaptively, and over extended periods of time.

Context helps agentic AI make informed decisions. It includes the task description (e.g., goals, constraints, priorities), environmental information (e.g., current data, user interactions), and the history of previous actions and outcomes. Context is often dynamically updated and considered with each new decision.

Memory allows agents to retain and reuse information over time. Short-term memory includes the current session or task history, while long-term memory stores facts, user preferences, and past results. Technically, memory is often implemented using vector databases.

Feedback is used by agentic AI to improve and adapt. It processes explicit feedback (e.g., “This result wasn’t helpful”) and implicit feedback (e.g., click behavior, success metrics). Agents can evaluate their own outputs and replan accordingly—this is known as self-evaluation. Feedback is used to adjust strategies, correct errors, or select new tools.