The verdict in three sentences
For an IT services firm answering more than 50 public tenders a year, an AI assistant connected to your document base (case studies, CVs, winning bids) is one of the most profitable AI investments of 2026. Budget 15,000 to 35,000 EUR to build, plus 50 to 300 EUR a month in API costs. Human review remains mandatory: the AI produces a structured, sourced first draft, and your bid team turns it into a winning response.
Where the time goes in a tender response
The sales director of a 200-consultant firm in Dublin handling 150 responses a year, at 3 days per technical proposal, ties up 450 person-days of presales. Much of that time is not high-value writing: it is reading tender documents on eTenders or TED, hunting for references and tailoring CVs.
| Response step | Current average time | With AI assistant | What the AI does |
|---|---|---|---|
| Tender document analysis (RFT, specs, terms) | 4 h | 1 h | extracts criteria, weightings, required documents, dates |
| Bid or no bid | 1 h | 0.5 h | fit score against your references |
| Finding similar references | 3 h | 0.5 h | retrieves the 5 closest projects |
| Selecting and tailoring CVs | 4 h | 1.5 h | suggests profiles, rewrites against the spec |
| Writing the technical proposal | 10 h | 5 h | structured first draft following the required outline |
| Review and compliance | 2 h | 2 h | automatic checklist, human review unchanged |
| Total per response | 24 h | 10.5 h | about 56% time saved |
These gains match the 40 to 60% range seen in 2026 on well-fed projects. Without a clean document base, they drop below 25%.
What a custom assistant costs
The typical architecture relies on RAG (retrieval-augmented generation): your documents are chunked and indexed in a vector database, and the language model only writes from retrieved extracts, citing its sources.
| Item | 2026 range | Comment |
|---|---|---|
| Scoping and document clean-up | 3,000 to 6,000 EUR | sorting bids, references, CVs, certificates |
| Ingestion pipeline and vector database | 4,000 to 8,000 EUR | PDF, Word, automatic refresh |
| Automatic tender analysis | 3,000 to 7,000 EUR | criteria and expected outline extraction |
| Drafting interface and Word export | 4,000 to 10,000 EUR | section-by-section generation, clickable sources |
| Security, SSO and logging | 1,000 to 4,000 EUR | EU hosting, team permissions |
| Total build | 15,000 to 35,000 EUR | 8 to 14 weeks |
| Language model API | 50 to 300 EUR per month | depends on volume and model |
| Hosting and maintenance | 300 to 800 EUR per month | updates, minor changes |
For sensitive contracts (defence, health, personal data), favour a model hosted in Europe with a contractual no-training commitment on your data.
Safeguards that prevent a rejected bid
A proposal generated without control can cite a reference that does not exist or promise a service level you cannot meet. Three rules apply. First, every factual claim (client reference, certification, headcount) must link to a source document. Second, a bid reviewer validates each section before export. Third, track your win rate before and after: on 150 responses a year, moving from 22% to 26% of contracts won matters far more than the time saved.
Also check the tender instructions: some public buyers now ask bidders to declare the use of AI tools in drafting. A short statement in the response is usually enough.
Mini case study
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Thomas, sales director of a 200-consultant IT services firm in Dublin, handles 150 tenders a year. At 24 h per response and a loaded cost of 75 EUR an hour, presales costs 270,000 EUR a year. With a 28,000 EUR assistant and 6,000 EUR of yearly running costs, he drops to 10.5 h per response: 117,000 EUR. The gross gain reaches 153,000 EUR in year one. Thomas reinvests part of the freed time to answer 40 more tenders. At a 22% win rate and an average contract of 180,000 EUR, that is about 9 extra contracts.
FAQ
Aren't ChatGPT or Copilot enough?
They help rephrase, but they know neither your references nor your CVs and do not cite sources. A dedicated RAG tool cuts time by 40 to 60%, compared with 10 to 20% for a general assistant.
Are our proposals used to train the model?
No, if you use a business API with a no-training clause, standard in 2026. Documents stay in your vector database hosted in the EU.
How many documents do we need to start?
Around thirty recent proposals, 50 project references and up-to-date CVs are enough for useful results. Document clean-up often represents 20% of the budget.
Can a public buyer reject a bid written with AI?
Not on that ground alone, unless the tender instructions say otherwise. The real risk is generic or inaccurate content, hence mandatory human review.
What ROI should we expect?
For 150 responses a year, payback takes 2 to 4 months on time savings alone. Below 40 responses a year, a SaaS tool at 300 to 800 EUR a month is often a better fit.
Let's scope your project. We audit your library of bids and references, price a RAG assistant sized to your volume (15,000 to 35,000 EUR) and deliver it in 8 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.
