Supporting 14 countries with one AI: how Vantage EU cut support costs 60% while going multilingual.

Vantage EU sells to mid-market enterprises across 14 European countries. Support queries arrive in German, French, Dutch, Polish, Spanish, and eight other languages — each requiring agents with native fluency. Hiring multilingual agents at enterprise-quality levels was expensive and slow.

Their previous solution was a patchwork: one Intercom chatbot per language, each with a separately maintained knowledge base. Keeping 14 knowledge bases in sync meant documentation updates took weeks to propagate and inconsistent answers were common. CSAT varied wildly by region, ranging from 3.1 (Polish) to 4.5 (German).

The company had also recently launched a GDPR compliance module and a new billing model — two changes that generated a surge in support volume that overwhelmed their team for three months.

Vantage EU's integration ran across HubSpot (CRM), Intercom (escalation), and their internal developer documentation portal. The key architectural decision was to maintain a single multilingual knowledge base rather than per-language silos.

UnifiedRAG's multilingual RAG pipeline indexes content in the source language (primarily German and English) and responds in the customer's detected language without translation artifacts. Vantage EU loaded 620 knowledge articles, their full API documentation, and GDPR compliance FAQ into the vector index.

The rollout was phased by language: German and English first (days 1–5), then French, Dutch, and Spanish (days 6–10), then the remaining nine languages (days 11–20). Each phase included a monitoring review before proceeding. Full 14-country coverage was live in three weeks.

Six months post-deployment, Vantage EU's results are striking: a single AI layer now handles primary support for all 14 markets. The regional CSAT spread has collapsed from a 1.4-point gap to 0.2 points — every region now sits between 4.6 and 4.8.

The company did not backfill two support roles that opened through natural attrition, redirecting the salary budget to product engineering. Support cost as a percentage of ARR dropped from 8.2% to 3.3%.

The COO noted in an all-hands that the AI's ability to handle GDPR and billing questions — the two highest-volume query types — had removed the most painful part of their support backlog.