The verdict in three sentences
Buyers of a B2B software company in Luxembourg (CIOs at banks, heads of operations at fund managers, compliance officers) now put their first shortlisting questions to AI assistants like ChatGPT, often before opening a comparison site or booking a demo. A funded vendor that is missing from those answers, or described with a certification it does not hold, drops off the shortlist without ever knowing. AI visibility work should be decided as an investment in public credibility, priced on quote and measured through a dated record of the answers, with no promise of being recommended.
What do your buyers ask AI assistants, in three languages?
Luxembourg has one feature that changes everything for a software vendor: the same buying committee asks its questions in French, German and English, and the answers differ from one language to another. A dense financial centre, clients supervised by the CSSF and strict expectations on data hosting push the questions towards compliance far more than features.
| Question put to the AI | Who asks it | What the answer needs to rely on |
|---|---|---|
| "Which regulatory reporting tools for investment funds are used in Luxembourg?" | Head of operations at a ManCo | Public sector references, mentions in specialist press |
| "Which SaaS vendor hosts its data inside the European Union?" | DPO at an insurer | A precise security page on location and subprocessors |
| "Welche Software für Risikomanagement nutzen Banken in Luxemburg?" | German-speaking risk manager | Product pages genuinely available in German |
| "Is this vendor ISO 27001 or SOC 2 certified?" | CISO at a private bank | An attestation actually held, with scope and date |
| "How much does this platform cost per user per year?" | CFO | A pricing page or a public "from" range |
| "Which vendors help EU financial entities with DORA third-party requirements?" | Compliance officer | Factual content on resilience, no regulatory promises |
| "Does this software integrate with SAP, Microsoft 365 or Salesforce?" | CIO at an industrial group | An up-to-date integrations page naming connectors |
These questions show what the AI must find before it can name you: verifiable facts. The DORA regulation, applicable since January 2025 to EU financial entities, leads your clients to question the resilience of their ICT providers; a vendor publishing vague information on the topic is either ignored or summarised wrongly. This is not legal advice.
Why a competitor shows up and you do not
AI assistants like ChatGPT build their answers from what is published, consistent and repeated by others.
| Signal | What helps | What hurts |
|---|---|---|
| Consistent public information | Same name, address and description on the site, LinkedIn and directories | Three different descriptions depending on the source |
| Third-party mentions | Tech and finance press, software marketplaces, sector events | Only self-published content |
| Factual pages | One page per use case, a security page, an integrations page | Slogans with no figures or scope |
| Structured data | Organization and SoftwareApplication markup matching the text | Missing or contradictory markup |
| Customer reviews | Reviews on B2B platforms, where your contracts allow it | Anonymous, unverifiable testimonials |
| Freshness | Dated security page, public changelog | A certification announced but expired |
For a funded vendor, accuracy is the most sensitive point. An AI claiming you are SOC 2 certified while the audit is still under way exposes your sales team to an awkward question in a buying committee, and your investors to an inconsistent story. Publish only what you actually hold, with the date. On GDPR, your privacy notice and demo form are read too: a form collecting more than it needs is visible, and the CNPD remains the reference authority in Luxembourg.
What the work covers and what the market charges
In substance the work covers a few blocks: recording what AI assistants say today, making public information consistent, making product, security, integrations and pricing pages readable and factual, structuring data, encouraging legitimate third-party mentions, then tracking change. This is an emerging market: the ranges below are a 2026 ballpark drawn from typical quotes by European agencies and consultants, and they vary strongly with the number of languages.
| Item | 2026 ballpark (EUR excl. VAT) | Note |
|---|---|---|
| Initial diagnostic (30 to 60 questions, FR, DE, EN) | 2,500 to 6,000 | One-off, baseline for comparison |
| Making key pages consistent | 6,000 to 20,000 | Depends on pages and languages |
| Specialist German or English translation | 0.12 to 0.25 per word | Third-party cost |
| Monthly support (content, tracking, mentions) | 2,000 to 7,000 per month | Market assumption |
| Tech and finance press relations | 2,500 to 8,000 per month | Often billed separately |
| Quarterly answer record only | 800 to 2,500 per quarter | Useful after the clean-up |
At Kolonell this work is priced on quote, after reviewing your site, your target languages and your direct competitors.
Measuring: the dated record, nothing else
Need a professional website?
Kolonell builds websites that attract clients, optimized for the Sénégalese market. Free quote in 2 minutes.
The only honest measure is to ask the same list of questions, in the same languages, on fixed dates, and to archive the answers. Three indicators are enough to steer: the share of answers mentioning your company, the accuracy of what is said (certifications, pricing, integrations, hosting) and the sources cited.
Mini case study
Illustrative example: Lumen Ledger, a Luxembourg vendor of a reporting tool for fund managers, after a funding round. The team records 40 questions in three languages, so 120 answers. Lumen Ledger appears in 9 answers, or 7.5%, and 3 of those 9 credit it with an ISO 27001 certification it is still working towards, so one third are wrong. Budget based on market rates: EUR 4,000 for the diagnostic and EUR 12,000 for the clean-up, EUR 16,000 in total. With a hypothetical average annual contract of EUR 32,000, the spend equals half a contract: management sees it as worthwhile if the errors disappear from the answers at the next record, six months later.
FAQ
Can we be assured that ChatGPT will recommend our software?
No, and any provider promising it should worry you. Your information can be made clearer, more consistent and more widely repeated; the effect is measured on a record of 30 to 60 questions, with no commitment on the outcome.
How long before the answers change?
Expect a ballpark of 3 to 6 months to see a shift on factual questions, longer for comparison questions. A quarterly record, so 4 data points a year, is enough to follow the trend.
Do we need to publish our prices to be cited?
It is not mandatory, but a range or a "from" price stops the AI from inventing a figure. Without public information, a sizeable share of pricing answers is either empty or wrong.
Which languages should we prioritise in Luxembourg?
For B2B software, French, German and English cover most queries; Luxembourgish rarely matters at this stage. Each added language multiplies the record: 40 questions in 3 languages means 120 answers to archive.
Can we name our banking clients?
Only with their written consent, and many contracts forbid it. A precise anonymised case study (sector, volume processed, rollout time) is often picked up better than a wall of logos.
Find out how AI assistants describe your firm. A first record in French, German and English shows where your company appears and what is said about your certifications. Request a diagnostic quote: reply within 48 hours.
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.
