AI agents for business — what they are and how to deploy
An AI agent isn't a chatbot. It's an employee that makes decisions, uses tools and acts autonomously. How to build and deploy one.
An AI agent has a goal (e.g. 'book a demo with this lead') and picks its own steps: checks the CRM, sends an email, proposes a calendar slot, updates notes.
Architecture: LLM (GPT-4.1 / Claude / Gemini) + tool calling + memory (vector DB) + orchestration (LangGraph, n8n, custom code) + guardrails.
Typical agents: sales (lead → demo), support (ticket → solution), operations (invoice → bookkeeping), research (query → report).
Pitfalls: hallucinations, missing audit trail, token costs. Fix: log every decision, run evals, set spend limits, human-in-the-loop for critical ops.
We deploy agents from €7k to €35k. ROI in 3–9 months depending on the scope of work replaced.
