The verdict in three sentences
A RAG-based AI chatbot — one that answers from *your* documents, not generic canned replies — costs 8,000 to 20,000 EUR to set up and 50 to 200 EUR/month to host, plus a variable 0.10 to 0.50 EUR per conversation. Expect 4 to 8 weeks from kickoff to production. The return comes from a 30-40 % drop in level-1 tickets and 24/7 availability with no added headcount cost.
What you actually pay for
An AI chatbot's price breaks into three blocks: setup (design, knowledge-base ingestion, integration with your site and tools), usage cost of the language model (billed per token, converted here to a per-conversation cost), and hosting + maintenance. A classic mistake is to look only at setup and discover usage cost once volume ramps up.
| Line item | 2026 range (EUR) | Note |
|---|---|---|
| Scoping + conversation design | 1,500 - 4,000 | Flows, tone, escalation cases |
| Knowledge-base ingestion (RAG) | 2,500 - 7,000 | Cleaning, chunking, indexing |
| Site + CRM/helpdesk integration | 2,000 - 6,000 | Widget, history, human handoff |
| Tests + guardrails (hallucinations) | 1,000 - 3,000 | Filters, "I don't know" replies |
| Hosting + monitoring / month | 50 - 200 | Vector store, logs, supervision |
| LLM usage cost / conversation | 0.10 - 0.50 | Depends on model and length |
No-code vs custom RAG: which to pick?
A no-code platform starts fast and is cheap to enter, but caps out on domain accuracy and gets expensive at volume. A custom RAG chatbot needs a higher upfront investment, but its marginal cost stays controlled and answer quality rises with your data.
| Criterion | No-code platform | Custom RAG |
|---|---|---|
| Setup (EUR) | 0 - 3,000 | 8,000 - 20,000 |
| Monthly subscription | 100 - 800 | 50 - 200 + usage |
| Accuracy on your data | Medium | High |
| Data control | Limited | Full (EU hosting) |
| Profitable volume | < 500 conv./month | > 1,000 conv./month |
| Tone customization | Low | Strong |
Simple rule: under 500 conversations/month with simple questions, no-code is enough; beyond that, or as soon as compliance and quality matter, custom RAG becomes more profitable.
Mini case study
Sophie runs customer service at a B2B e-commerce SME in Nantes: 3,200 tickets/month, of which 60 % are level 1 (order tracking, availability, returns). An agent handles a ticket in 6 minutes on average, loaded cost 28 EUR/h.
Current monthly cost of level-1 tickets: 3,200 × 60 % = 1,920 tickets × 0.1 h × 28 EUR = 5,376 EUR/month. The RAG chatbot (14,000 EUR setup) deflects 40 %, i.e. 768 tickets, at a usage cost of 768 × 0.30 EUR + 150 EUR hosting = ~380 EUR/month. Net saving: ~1,770 EUR/month. Setup pays back in ~8 months, 24/7 availability included.
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FAQ
How long to get an AI chatbot into production?
Expect 4 to 8 weeks for a RAG project: 1-2 weeks of scoping, 2-4 weeks of ingestion and integration, then a testing phase. A no-code bot can go live in days but with lower accuracy.
Isn't the per-conversation cost expensive in the end?
At 0.30 EUR per conversation, 2,000 conversations cost 600 EUR/month in LLM usage. Compared to agent hours saved, the break-even is reached within a few hundred automated tickets.
How do you avoid made-up answers (hallucinations)?
RAG mode restricts the model to your documents, and we add guardrails that force an "I don't know" and a human handoff. A solid setup spends 1,000 to 3,000 EUR on these tests.
Does my data stay confidential?
In custom builds, we host the vector store and logs in the EU and pick an LLM provider committed to not reusing your data. This is a point to lock into the contract at quote stage.
Can we start small and expand?
Yes: we start on one scope (e.g. order tracking), measure the resolution rate, then add topics. It's the best way to secure ROI.
Let's scope your project. Tell us your monthly ticket volume, your document sources and your current helpdesk, and we'll define the scope and an indicative budget. Detailed quote within 48 h. WhatsApp +221 77 596 93 33.
Mohamed Bah
Fondateur, Kolonell
Passionate about digital and entrepreneurship in Africa, Mohamed has been helping Sénégalese businesses with their digital transformation since 2020. Founder of Kolonell, he believes every SME deserves a professional and accessible online présence.
