The verdict in three sentences
An internal AI assistant built on RAG (retrieval-augmented generation over your documentation) costs between 6,000,000 and 14,000,000 FCFA (~9,150-21,350 EUR) in production in 2026, preceded by a POC at 2,500,000-5,000,000 FCFA. The recurring LLM API cost runs from 40,000 to 250,000 FCFA/month depending on volume, plus 12 to 18 %/year maintenance. Typical ROI: -35 % N1 tickets, 2 to 4 h/day saved per agent, and response times falling from 8 min to 20 s.
The end-to-end budget
| Stage | 2026 range (FCFA) | Deliverable |
|---|---|---|
| RAG POC (proof of value) | 2,500,000 - 5,000,000 | Prototype on a limited corpus |
| Production + vector database | 6,000,000 - 14,000,000 | Integrated, secured assistant |
| Support / intranet integration | 1,500,000 - 4,000,000 | Widget, SSO, logging |
| LLM API (recurring) | 40,000 - 250,000 /month | By query volume |
| Annual maintenance | 12-18 % of build | Corpus and prompt updates |
The vector database and document ingestion (cleaning, chunking, indexing) is the most underestimated technical line: without a clean corpus, the assistant hallucinates and loses the team's trust.
Custom build vs SaaS chatbot editor
| Criterion | SaaS chatbot | Custom assistant (RAG) |
|---|---|---|
| Entry cost | 30 - 300 EUR/month (~20,000-200,000 FCFA) | 6,000,000 - 14,000,000 FCFA |
| Private knowledge base | Limited | Complete (your documents) |
| Data control | Low | Total (controlled hosting) |
| Business customization | Low | High |
| Cost at high volume | Grows fast | Controlled API |
| Best for | Simple FAQ | N1 support, rich internal docs |
A SaaS editor is enough for a public FAQ. As soon as you must query rich internal documentation, guarantee confidentiality and genuinely cut N1 support load, custom wins.
12-month projection
| Item | Amount (FCFA) |
|---|---|
| Build (production) | 9,000,000 |
| LLM API (12 months × 120,000) | 1,440,000 |
| Maintenance (15 %) | 1,350,000 |
| Total year 1 cost | 11,790,000 |
| Support saving (see case) | ~19,500,000 |
| Net gain year 1 | ~7,700,000 |
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Mini case study
Ousmane, CEO of a services SME in New York (45 staff), deploys an internal AI assistant for N1 support. Before: 3 agents handled 1,200 tickets/month, average response 8 min. After: -35 % tickets (self-service answers), time cut to 20 s for covered cases, i.e. about 2.5 h/day saved per agent. Valued at a loaded cost of 350,000 FCFA/month/agent, the reallocated time is nearly 1,625,000 FCFA/month, i.e. 19,500,000 FCFA/year — a payback of 7 to 8 months against an 11,790,000 FCFA first-year build.
FAQ
Do I need a POC before committing? Strongly recommended. A POC at 2,500,000-5,000,000 FCFA validates answer quality on your corpus before committing the production budget.
What is the real recurring cost? Mainly the LLM API: 40,000 to 250,000 FCFA/month depending on query volume, plus 12 to 18 %/year to maintain corpus and prompts.
Can the assistant hallucinate? The risk exists, but RAG strongly reduces it by grounding each answer in your source documents and citing the reference. Corpus quality is decisive.
Does my data stay confidential? Yes, with a controlled architecture: private vector database, controlled hosting, and LLM providers that don't train on your data under the chosen terms.
How long to go to production? 2026 order of magnitude: 6 to 12 weeks after a conclusive POC, support integration and SSO included.
Let's scope your project. Describe your ticket volume, internal documentation and support tools: we'll frame a POC then a production budget between 6,000,000 and 14,000,000 FCFA. 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.
