The verdict in three sentences
In 2026, integrating applied AI into a specific business use case costs between 2,500,000 and 15,000,000 FCFA depending on complexity, with most SMEs starting under 6,000,000 FCFA on a single profitable use case. The cheapest path almost always goes through APIs (Claude, OpenAI) rather than training your own model. The success factor isn't the model but data quality and scoping a high-volume use case.
Cost per use case
The classic mistake is wanting to "do AI" in general. You integrate one precise, measurable, high-volume use case. Below are 2026 orders of magnitude.
| Use case | Integration cost (FCFA) | Usage/mo | Timeline |
|---|---|---|---|
| Quote/email drafting assistant | 2,500,000 - 4,500,000 | 60,000 - 200,000 | 3 - 5 wks |
| Data extraction from invoices/contracts | 4,000,000 - 8,000,000 | 100,000 - 350,000 | 5 - 8 wks |
| Request classification and routing | 3,500,000 - 7,000,000 | 80,000 - 300,000 | 4 - 7 wks |
| Document search (internal RAG) | 5,000,000 - 10,000,000 | 150,000 - 500,000 | 6 - 10 wks |
| Recommendation / scoring | 6,000,000 - 15,000,000 | 200,000 - 700,000 | 8 - 14 wks |
The monthly usage cost (API tokens) stays modest against the gains: for most SMEs it sits between 60,000 and 500,000 FCFA/mo in 2026.
Build vs API: the real trade-off
The temptation to train your own model is almost always an economic trap for an SME. Here's the 2026 comparison.
| Criterion | API (Claude/OpenAI) | Custom-trained model |
|---|---|---|
| Upfront cost | 2.5 - 15 M FCFA | 25 - 80 M FCFA |
| Implementation time | 3 - 14 wks | 4 - 9 months |
| Immediate quality | very high | variable |
| Monthly cost | tokens (60k - 500k) | GPU + MLOps (500k+) |
| Fit for an SME | yes | rarely |
In over 90% of SME business cases, an API with RAG and good prompt engineering beats a homegrown model, at 5 to 10 times lower cost and lead time. Custom builds are only justified for massive volumes or extreme confidentiality constraints.
Mini case study
Me Diop, partner at a 12-person law firm in Dublin, watched his lawyers spend 3 h per file extracting key clauses from contracts and drafting summaries. Kolonell integrates an assistant based on the Claude API with RAG over the firm's document base: clause extraction, summary and a first-draft memo.
Budget: 6,800,000 FCFA, delivered in 7 weeks, plus 250,000 FCFA/mo usage. Gain: 1 h 45 saved per file across 40 files/mo, i.e. 70 h/mo. At a loaded cost of 12,000 FCFA/h, that's 840,000 FCFA/mo saved, payback in about 9 months, and the capacity to handle more files without hiring.
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FAQ
How much for a serious first applied-AI project?
From 2,500,000 FCFA for an assistant on a simple case (drafting, classification), and 4 to 8 million FCFA for extraction or document RAG. Below that, you stay on feasibility tests without production deployment.
Should we train our own AI model?
Almost never for an SME: custom training costs 25 to 80 million FCFA and 4 to 9 months. Claude or OpenAI APIs with RAG deliver higher quality at 5 to 10 times lower cost.
What monthly usage cost should we expect?
Between 60,000 and 700,000 FCFA/mo depending on volume and use case. This cost is proportional to usage and stays marginal against hours saved.
Is our data safe?
Yes, with clear governance: we scope which data is sent to APIs, anonymise the sensitive parts and can host the RAG layer internally. Compliance with the 2008-12 personal-data law is built into scoping.
How long to production?
From 3 weeks for a simple assistant to 14 weeks for a scoring or recommendation system. Data preparation and cleaning often account for half the timeline.
Let's scope your project. Describe the high-volume use case you want to automate and your data format: we'll price the integration, monthly usage and ROI. 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.
