How a biomass boiler manufacturer went from one static page to a 6-language AI platform

Tatano manufactures biomass boilers and sells across four European markets. At the start of 2026, they had a single French-language website with no automation, no chatbot and no organic content strategy. Six months later, they operate a fully autonomous digital presence that generates leads while the sales team sleeps.

The starting point: one market, one language, no automation

The challenge was not technical — it was structural. Four distinct markets (Luxembourg, Belgium, France, Switzerland) each with their own language mix, subsidy schemes and buyer profiles. Building one generic site for all of them would have meant serving none of them well. The answer was a multi-domain architecture: tatano.lu, tatano.be, tatano.fr and tatano.ch, each resolving with its own canonical URLs, hreflang signals, sitemap and robots.txt — all from a single Next.js codebase that reads the Host header at runtime.

6 languages, 0 manual translations

Product pages, FAQ, legal notices and chatbot responses are available in French, English, Dutch, German, Italian and Luxembourgish. All content variants are generated and reviewed once, then served from the same database. The product catalogue — 230 source files, 468 commits — covers every boiler model with energy class labels, multilingual technical specs and SEO-structured descriptions. Time spent on per-market copy maintenance: zero.

Optimus: a lead chatbot in 7 languages, live in 4 countries

Optimus (V6, powered by MiniMax-Text-01) answers product questions 24/7 across all four domains. It retrieves answers from 33 indexed documents using semantic search (bge-m3 embeddings, pgvector), responds in the visitor's language and, when a lead is qualified, triggers an automated email sequence — two templates per domain, adapted per market. Response latency: 1.3–1.7 seconds. A sales team member answering the same question by email would take hours.

Daily autoblog: one article per country, every morning at 07:00

A cron job runs every morning: it queries Google Trends per market, picks the most relevant topic for that country and language, generates a structured article via a three-tier LLM pipeline (with automatic fallback if a provider degrades), publishes it to PostgreSQL, pushes it to IndexNow for immediate indexing and cross-posts to social channels. Luxembourg gets articles in French, English and Luxembourgish. Belgium in French and Dutch. France in French. Switzerland in French, German and Italian. Weekly content operations time for the client: zero hours.

Generative video: a campaign spot without a production crew

For product launch campaigns, we produce 15-second spots using Veo (Google) from a storyboard anchored on the real product photo. One multi-shot generation covers the full clip — no stitching, no post-production team. Voiceover is generated per language via ElevenLabs and mixed with licensed music. The client reviews a finished master, not a rough cut.

What six months of compounding automation looks like

468 commits. Four live country domains. Six languages. One AI chatbot handling leads around the clock. A daily article per market. Three Google Ads campaigns in Belgium (102 keywords, 300–500 € / month). Every piece built to run without a content team — because Tatano doesn't have one.

Token cost vs. Belgian human equivalent

A digital agency quoting this project from scratch — 4-country multilingual platform, RAG chatbot, daily autoblog, video pipeline, ad campaigns — would invoice €60,000–90,000 for the initial build plus €4,000–6,500 per month for a content manager, part-time developer and support role. The AI infrastructure that replaces this: the autoblog pipeline (Claude Sonnet 4 primary, NVIDIA NIM llama-3.3-70b fallback) generates 240 articles per month for approximately €12 in API costs; Optimus (MiniMax-Text-01, 33 indexed documents, bge-m3 embeddings via NVIDIA NIM) handles thousands of chatbot conversations for under €5; the VPS hosting everything costs €12/month. Total monthly AI infrastructure: €30–55. At a Belgian mid-level employee rate of €70/hour, the 90+ hours per month of content production, chatbot support and development maintenance eliminated by this stack represents €6,300/month in avoided labour. Annual equivalent: over €75,000 in labour savings against under €700 in AI spend — a ratio above 100:1.