AI Agents

Your team is building AI demos that never ship to production

I build production-grade AI agents and multi-agent platforms that run reliably at enterprise scale — with monitoring, guardrails, and real ops integration.

01

Sound familiar?

If any of these hit close to home, you're not alone. This is where most technical leaders get stuck.

Your proof-of-concept impressed the board, but six months later it still isn't in production

The AI vendor demos look great — until you try to integrate with your actual data and systems

Your engineers are smart but nobody on the team has shipped multi-agent systems before

You're burning budget on consultants who deliver PowerPoints, not working software

Definition

What is AI Agents?

Agentic AI systems are autonomous software agents powered by large language models that can reason, plan, use tools, and take actions — independently or in coordinated multi-agent pipelines. Unlike simple chatbots, production AI agents integrate with real enterprise systems, handle edge cases gracefully, and operate under monitoring and governance frameworks.

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How we work together

A structured process that reduces risk and gives you visibility at every step.

01

Discovery

Map your current systems, data sources, and the specific workflows you want to automate. No generic assessments — I focus on what will move the needle.

02

Architecture

Design the agent topology, tool integrations, monitoring hooks, and guardrails. You get a concrete architecture document, not a vague roadmap.

03

Build

Hands-on development of the agent pipeline, integration with your existing stack, and deployment to your infrastructure.

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Handoff

Knowledge transfer, documentation, and monitoring setup so your team can operate and extend the system independently.

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What you get

Concrete deliverables, not vague promises.

01

Production-grade AI agents running on your infrastructure — not demo notebooks

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Multi-agent orchestration with Langflow, OpenWebUI, or custom pipelines

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Integrated monitoring via Grafana/Prometheus with anomaly alerting

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Your team trained to maintain and extend the system

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Technologies I work with

Langflow OpenWebUI LLM Agents Grafana Prometheus Python Kubernetes RAG Vector DB
Investment

Typical investment

Depends on scope, timeline, and complexity. Let's discuss your specific situation.

EUR 25,000 - 80,000

per project

05

Common questions

Ready to ship your AI project?

Let's have a 30-minute conversation about your challenge. No pitch, no pressure — just an honest assessment of whether this is the right approach for you.

Let's Talk on LinkedIn
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