AI Pirates
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AI Pirates
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// AI Agents Protocol

AI Agents.
Autonomous systems that work for you.

Not a chatbot. Not a copilot. An AI agent plans autonomously, uses tools, makes decisions, and executes multi-step workflows on its own. We build these systems — production-ready, GDPR-compliant, on your servers.

Agentic AI ReAct Pattern Tool Use Multi-Agent GDPR-compliant

// Evolution

Chatbot vs. Copilot
vs. AI Agent.

Chatbot / Copilot

Only responds to direct inputs
Cannot use tools or APIs
No memory across sessions
Cannot plan or prioritize
Requires permanent human supervision

AI Agent

Autonomously plans multi-step workflows
Uses APIs, databases, web, email
Long-term memory via vector DBs
Decides and prioritizes autonomously
Works 24/7 without human oversight

The core: An AI agent uses the ReAct pattern — Reason (think), Act (execute), Observe (evaluate), Loop (repeat). Orchestrated by LangChain or LangGraph, an agent can decompose complex tasks into subtasks and process them sequentially.

// Use Cases

AI Agents
for every department.

Customer Service Agent

24/7 ticket handling, intelligent routing, knowledge base access. Resolves level-1 requests autonomously and escalates only when needed. Integration with Zendesk, Freshdesk, Intercom.

Marketing Agent

Content creation, campaign management, A/B test evaluation, performance reporting. Learn more on our Agentic Marketing page.

Sales Agent

Lead qualification, CRM maintenance, follow-up sequences, meeting scheduling. The agent scores leads, enriches data, and prioritizes the sales funnel.

Operations Agent

Process automation, system monitoring, anomaly detection, automated reporting. Runs via n8n workflows on your servers.

Research Agent

Market analysis, competitive intelligence, data extraction, trend monitoring. Searches sources, aggregates data, and delivers structured insights.

Code Agent

Code review, automated testing, deployment pipelines, documentation. Supports development teams with repetitive engineering tasks.

// Architecture

How we build
AI Agents.

LLM LAYER

GPT-4, Claude, Llama, Mistral

ORCHESTRATION

LangChain, LangGraph, n8n

TOOLS

APIs, DBs, Web, Mail, Slack

MEMORY

Vector DBs, RAG

DEPLOYMENT

Docker, EU Servers, GDPR

01

Use Case & Scope

What tasks should the agent handle? What tools does it need? What does the ideal workflow look like? We define the scope together — more about our consulting approach.

02

Architecture & Tech Stack

LLM selection, orchestration framework, tool integration, memory strategy. Open source where possible, commercial APIs where necessary.

03

Build & Test

Iterative build: agent logic, prompt engineering, tool connections, guardrails. Testing with real data and edge cases.

04

Deploy & Monitor

Deployment on your infrastructure. Monitoring, logging, alerting. The agent works autonomously — you maintain full control.

05

Scale & Optimize

Connect new tools, launch additional agents, build multi-agent systems. Continuous optimization based on real performance data.

// FAQ

Frequently Asked Questions
About AI Agents.

What is the difference between a chatbot and an AI agent?

A chatbot responds to inputs with predefined answers. An AI agent plans autonomously, uses tools (APIs, databases, web), makes decisions, and executes multi-step workflows — e.g., analyzing a customer inquiry, looking up data in the CRM, developing a solution, and sending a personalized response.

What tasks can an AI agent handle?

Repetitive, rule-based, or data-intensive tasks: customer service (24/7 tickets), marketing (content, campaigns), sales (lead scoring, CRM), operations (monitoring, reporting), and research (market analysis, data extraction).

How long does AI agent development take?

Simple agents (FAQ bot with knowledge base): 1-2 weeks. Complex multi-agent systems: 4-8 weeks. We work iteratively — the first functioning agent often stands after a few days.

Are AI agents GDPR-compliant?

Yes — with the right architecture. We use EU hosting, self-hosted LLMs (Mistral, Llama via Ollama), data processing agreements, and data minimization. More about our GDPR-compliant AI automation.

Can an AI agent work with our existing systems?

Yes. AI agents integrate via APIs: CRM (HubSpot, Salesforce), ERP, databases, email, Slack, Google Workspace. Orchestration runs via n8n or LangChain.

What does an AI agent cost?

Simple agents from 5,000 EUR, complex multi-agent systems 15,000-40,000 EUR. Ongoing token costs typically 50-500 EUR/month depending on volume. We optimize for token efficiency and use open source where possible.

// Start Building

Ready for
autonomous AI?

30-minute Discovery Call — free of charge. We identify the ideal use case for your first AI agent and sketch the architecture.

Book Discovery Call