The verdict in three sentences
An internal knowledge base with RAG AI (retrieval-augmented generation) lets staff ask a question in plain language and get a sourced answer drawn from your own documents. For an engineering firm of 120 engineers in Singapore sitting on 15 years of reports, calculation notes and lessons learned, the realistic gain is 3 hours per engineer per month. The project costs EUR 15,000 to 40,000 (about USD 16,300 to 43,500), plus EUR 200 to 800 a month in API fees, with two non-negotiable requirements: access rights enforced and hosting in a controlled region.
How enterprise RAG works, and what drives the price
The principle: documents are split into passages, turned into vectors and stored in a dedicated database. For each question, the system retrieves the 5 to 15 most relevant passages, then a language model writes an answer citing its sources (document, page, date). The engineer clicks the source to check.
Budget depends mostly on the number and nature of documents, the sources to connect and the granularity of access rights.
| Scope | Indexed volume | Connected sources | Upfront cost | Lead time |
|---|---|---|---|---|
| Single-team pilot | 5,000 documents | 1 (SharePoint or file server) | EUR 15,000 to 20,000 | 4 to 6 weeks |
| Full engineering firm | 50,000 documents | 2 to 3 (SharePoint, DMS, wiki) | EUR 25,000 to 32,000 | 8 to 10 weeks |
| Multi-site with drawings and scans | 50,000 documents + 10,000 drawings | 3 to 5, with OCR | EUR 32,000 to 40,000 | 10 to 14 weeks |
| Inherited access rights option (Active Directory, Entra ID) | Any scope | Group sync | + EUR 3,000 to 6,000 | + 2 weeks |
| Teams assistant option | Any scope | Teams interface | + EUR 2,500 to 4,000 | + 1 to 2 weeks |
Technical documents (scanned PDFs, tables, annotated drawings) need OCR and specific chunking: that is often where answer quality is won or lost.
Recurring costs and hosting choices
| Monthly item | 2026 range | What drives it |
|---|---|---|
| Language model API | EUR 200 to 800 | Number of questions (2,000 to 10,000 a month) and answer length |
| Vector database and server | EUR 150 to 400 | Indexed volume, redundancy |
| Re-indexing new documents | EUR 30 to 100 | Frequency (daily or weekly) |
| Monitoring and maintenance | EUR 300 to 800 | Service level, model updates |
| Monthly total | EUR 680 to 2,100 | For 120 active users |
For a firm working on government or defence projects, hosting in Singapore under the PDPA is a prerequisite, sometimes with a language model hosted in a local cloud region or on an internal server. A self-hosted open-source model removes the API bill but needs a GPU server at EUR 800 to 2,000 a month.
Access rights: where projects fail
A poorly designed RAG can answer an intern with an excerpt from a confidential file. The rule: the tool must never show a passage the user could not open in the original folder. Technically, each indexed passage carries the rights of its source document, and filtering happens before the answer is generated.
| Control level | Principle | Residual risk | Extra cost |
|---|---|---|---|
| No filter | Everyone sees everything | High, avoid | EUR 0 |
| Filter by document space | One index per team | Medium | EUR 1,500 to 3,000 |
| Rights inherited per document | AD or Entra ID sync | Low | EUR 3,000 to 6,000 |
| Inherited rights + query log | Full traceability | Very low | EUR 4,500 to 8,000 |
| Sensitive projects excluded | Export-controlled files kept out of index | Very low | EUR 1,000 to 2,000 |
Mini case study
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Wei Ling, technical director of a structural engineering firm in Singapore (120 engineers), estimates each engineer spends about 6 hours a month hunting for a calculation note, lesson learned or test report. The RAG project indexes 50,000 documents for EUR 28,000, with EUR 1,200 a month in recurring costs.
With a cautious 60 % adoption rate (72 engineers) and a gain of 3 hours a month each, the firm recovers 216 hours a month. At a loaded cost of EUR 55 an hour, that is EUR 11,880 a month. Net monthly gain reaches about EUR 10,700, so the investment pays back in under 3 months. The less visible benefit matters just as much: junior engineers can tap the knowledge of retired seniors.
FAQ
How much does a RAG AI knowledge base cost?
Budget EUR 15,000 to 20,000 for a single-team pilot and EUR 25,000 to 40,000 for 50,000 documents across several sources. Recurring costs range from EUR 680 to 2,100 a month for 120 users.
Does the AI make up answers?
The risk exists but is reduced: the system answers only from retrieved passages and cites its sources. On a well-indexed corpus, the rate of correct, sourced answers usually exceeds 85 %.
Are our confidential documents protected?
Yes, with rights inherited per document and controlled-region hosting. Sensitive files can be excluded from the index for an extra EUR 1,000 to 2,000.
Can we avoid sending data to an overseas provider?
Yes, by using a model hosted in a local cloud region or an open-source model on your own GPU server, from EUR 800 a month.
How long until first results?
A pilot on 5,000 documents is live in 4 to 6 weeks. Full rollout on 50,000 documents takes 8 to 14 weeks depending on the share of scans to process.
Let's scope your project. Tell us your document volume, sources (SharePoint, DMS, file server) and confidentiality constraints: we will price a pilot or full rollout between EUR 15,000 and 40,000, in 4 to 14 weeks. 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.
