The verdict in three sentences
A properly built AI support chatbot on your documentation costs 12,000 to 30,000 EUR in London in 2026, delivered in 6 to 8 weeks. The real value is not the API cost (0.002 to 0.01 EUR per request) but the 40 to 60% ticket deflection rate, which frees up half to a full support FTE. The trap: a chatbot without RAG architecture hallucinates and destroys customer trust within three days.
What a RAG AI chatbot really costs
The cost splits between initial build (one-off) and monthly running (API + hosting + maintenance). A "RAG" (Retrieval-Augmented Generation) chatbot fetches the answer from YOUR documents before replying, which prevents made-up answers.
| Item | 2026 range (EUR) | Type |
|---|---|---|
| Scoping + documentation audit | 1,500 - 3,000 | One-off |
| Knowledge base integration (RAG) | 4,000 - 6,000 | One-off |
| Chatbot + widget development | 5,000 - 12,000 | One-off |
| Admin + supervision interface | 2,000 - 5,000 | One-off |
| Testing, guardrails, go-live | 1,500 - 4,000 | One-off |
| Project total | 12,000 - 30,000 | One-off |
| LLM API cost per request | 0.002 - 0.01 | Recurring |
| Hosting + vector database | 80 - 250 / month | Recurring |
| Maintenance + re-indexing | 300 - 900 / month | Recurring |
For an SME handling 3,000 conversations/month, the API cost is around 12 to 30 EUR/month: negligible against the human cost of a ticket.
Human ticket cost vs AI
This is where the ROI plays out. A ticket handled by an agent costs their loaded time; a ticket deflected by AI costs a few cents.
| Metric | 100% human support | With AI chatbot (50% deflection) |
|---|---|---|
| Tickets/month | 3,000 | 3,000 |
| Handled by humans | 3,000 | 1,500 |
| Avg cost/human ticket | 4.50 EUR | 4.50 EUR |
| Monthly human cost | 13,500 EUR | 6,750 EUR |
| Monthly AI cost (API+infra) | 0 | ~450 EUR |
| Total monthly cost | 13,500 EUR | 7,200 EUR |
| Monthly saving | — | ~6,300 EUR |
With a 20,000 EUR project, break-even is reached in just over 3 months.
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Mini case study
Sophie, customer service manager at an e-commerce SME in London (28 staff), receives 3,200 emails/month, 62% of them repetitive questions (order tracking, returns, delays). She invests 19,000 EUR in a RAG chatbot wired to her FAQ and order tool. Measured deflection after 2 months: 48%, i.e. 1,536 tickets absorbed. At 4.50 EUR per ticket, that is 6,912 EUR saved/month. Running cost: 520 EUR/month. Net monthly gain: ~6,400 EUR. ROI reached in 3 months, and her team refocuses on high-value disputes.
FAQ
Will an AI chatbot hallucinate and give wrong answers? With RAG architecture and guardrails ("I'll transfer you to an agent" when unsure), the hallucination rate drops below 2%. Without RAG, a raw LLM regularly invents answers: that is the main risk to budget for.
How long does it take to deploy? Expect 6 to 8 weeks: 1 to 2 weeks of scoping and documentation cleanup, 3 to 4 of RAG development, 1 to 2 of testing and running-in on real traffic.
What deflection rate is realistic? Between 40 and 60% depending on the quality of your knowledge base. A support desk where 60% of requests are repetitive can aim for the top of the range.
Is there a monthly subscription on top of the project? Yes: LLM API (0.002-0.01 EUR/request), hosting and vector database (80-250 EUR/month) and maintenance (300-900 EUR/month) to re-index as your documentation evolves.
Can we keep a human in the loop? Yes, and it is recommended: the chatbot handles tier 1 and automatically escalates complex cases to an agent, with the full conversation history.
Let's scope your project. Give us your monthly ticket volume, your 5 most frequent contact reasons and your current tool (Zendesk, Gorgias, email): we'll estimate realistic deflection and 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.
