An AI agent is a language model that uses tools and defined action steps to complete a task, for example checking data, querying a system, or preparing a next step. The difference from a chatbot: it does not only answer, it acts within defined boundaries. For SMEs, the right answer is usually not a fully autonomous agent, but a testable workflow with human approval for sensitive cases.

When does an SME need Machine Learning?

Machine Learning pays off when you have enough historical data and want to repeatedly derive a forecast, score, or anomaly from it. Good signals are many comparable cases, clear target values, and a decision that occurs often enough for learning to matter. If the data is missing, messy, or the decision follows a fixed rule, Machine Learning is usually the wrong place to start.

When is classical AI enough?

Classical AI is enough when the logic is known and the result must be guaranteed: prices, permissions, compliance, VAT, capacity, or routes. It is often better than generative AI because it stays traceable, inexpensive, and stable. In real solutions, it protects language models wherever creative freedom is not allowed.

RAG (Retrieval-Augmented Generation) connects a language model to your own documents. The model first retrieves relevant passages from manuals, contracts, or knowledge bases and then answers based on that material. This is useful when answers must be current, company-specific, and traceable to sources. RAG reduces hallucinations, but it does not replace clean data and document management.

Which AI automation suits SMEs?

The best starting point is rarely the most spectacular agent. SMEs benefit most from processes that happen often, have clear exceptions, and connect to existing systems: checking invoices, triaging requests, preparing quotes, or querying status. Start with a small, measurable automation and add more autonomy only when the case truly needs it.

How do we start if the use case is still unclear?

If several ideas are on the table, do not start with a prototype. Start with prioritization: clarify business value, data readiness, risk, integrations, and effort for each use case. That is what the AI Potential Analysis is for: it separates worthwhile cases from attractive ideas and produces a sequence that supports an investment decision.

Understanding AI Technology

We know AI. Which technology solves your problem?

Four AI approaches, no hype. Each solves a different kind of problem - the strongest ones combine several. Describe your task to the AI Advisor: it tells you honestly which technology fits.

Start with the AI Advisor ↓Or book an initial call

Classical AIRules & logic

Machine LearningPrediction from data

Generative AILanguage & content

AI AgentsThink & act

The AI Advisor

Describe your problem - we sketch the approach.

A few short questions, then we show you a rough first assessment: which AI technology (or combination) could solve your problem. Honest and without obligation.

Mat

KI-Technologie-Berater · Erste Einschätzung

Beta

Hallo, ich bin Mat, der KI-Berater von Quatico. Ich helfe Ihnen einzuordnen, welche KI-Technologie zu Ihrer Aufgabe passt — als erste, ehrliche Orientierung, nicht als Verkaufsgespräch. Beschreiben Sie kurz, was Sie lösen möchten; danach stelle ich ein, zwei kurze Fragen.

Frei beschreiben — oder ein Beispiel wählen.Enter ↵ sendet · Shift+Enter = neue Zeile

Beispiele

01 — The landscape

Four approaches. None of them is "the AI".

Each is strong in a different kind of problem. Tap on an approach for examples from everyday SME work and the right next step.

02 — Interplay

Real solutions combine several approaches.

Each step goes to the approach that does it best. Tap on a pattern for a concrete example.

How to recognize that a combination is needed: The process contains both a fuzzy step (language, judgment) and a step that must be exactly right (money, policy, a real action). No single approach is good at both - the deterministic guardrail is then non-negotiable.

03 — AI Agents in detail

"Agent" is not one thing - it's a ladder.

From simple and bounded to autonomous and open. Tap on a class for the right SME example and why it fits.

Most SME needs sit on the top three rungs - procedural. That's exactly where the AI Agent Workshop comes in: a working agent for your case, not a textbook example.

04 — Your path

From idea to a production-ready solution.

Still several candidates or an unclear order? Start with clarity. A clear use case? Build the agent.

Step 1 · Clarity

AI Potential Analysis

Structured, pragmatic, for Swiss SMEs. Prioritized use cases, a roadmap, and a report fit for the investment decision - including an exclusion list.

from CHF 1'290 · 2h to a full day

→Data room check and status assessment
→3–7 prioritized use cases with scoring
→Risk & compliance (DSG, EU AI Act)

View the AI Potential Analysis →

Step 2 · Implementation

AI Agent Workshop

Vendor-independent, tailored to your use case: we build the agent in advance as a working prototype - your team builds along and takes it into production.

CHF 18'000 – 160'000 · Solo to Orchestra

→Pre-built agent prototype on your platform
→Platform choice instead of platform lock-in (n8n, Make, Copilot …)
→Enablement as a deliverable - your team keeps building itself

View & request the workshop →

05 — Why Quatico

Engineering instead of consulting slides.

We understand Swiss SMEs.

The DACH market, German, Swiss data protection, Swiss realities. No generic decks.

We build what we recommend.

Primarily a software engineering firm. We recommend nothing we couldn't build ourselves - tool-neutral, without commissions.

Fixed price and guarantee.

You know in advance what it costs. With the Potential Analysis: money back if it doesn't produce three implementation-ready use cases.

To take away

The AI reference card for your management team.

One page that captures the four approaches, their combinations, and the agent classes in a nutshell - with SME examples. Ideal for creating a shared language internally before you invest.

We'll send you the PDF overview. No spam.

Common questions

Straight answers on the four AI approaches

Ready to build the right thing?

Michael

AI & Software Engineering

In a 30-minute call we clarify which approach - or which combination - fits your situation, with an eye on your data and compliance.

Book a call michael@quatico.com +41 43 543 90 50

We know AI. Which technology solves your problem?

Describe your problem - we sketch the approach.

Four approaches. None of them is "the AI".

Classical AI

Machine Learning

Generative AI

AI Agents

Real solutions combine several approaches.

Generate, then check

Predict, then communicate

The full stack

"Agent" is not one thing - it's a ladder.

Tool-augmented LLM

Workflow / chain

Router / orchestrator

Autonomous agent

Multi-Agent system