A bootstrapped SaaS was gaining customers in markets its two support agents couldn't read. We built a real-time translation layer inside their helpdesk — with a protected product glossary — so the same small team now supports customers in nine languages.
Typical results
2
Agents on the team
3 hrs
First response, non-English
4.7/5
CSAT on translated threads
Figures reflect typical results for this kind of automation.
The challenge
Nearly 40% of new signups came from Brazil, Japan and Europe, but the two-agent support team worked only in English and Hebrew. Non-English tickets meant copy-pasting through free translation tools that mangled product terms, and response times stretching past a day. Hiring native-speaking agents for every market was never going to happen on a bootstrapped budget.
Before and after
First response (non-English)
−88%Languages covered
4.5×The automation
We wired a translation layer directly into the existing helpdesk. Incoming tickets are language-detected and translated to English within seconds, appearing to agents as normal tickets with the original preserved alongside. When an agent replies, OpenAI translates back — passing through a protected glossary of 200+ product terms so feature names and technical phrasing stay exact, and matching the customer's formality level. Agents never leave the helpdesk or paste text anywhere.
How it works
- 01
Detect and translate inbound
Every incoming ticket is language-detected and translated to English in seconds, with the original preserved alongside.
- 02
Agents work as usual
The team reads and replies in English inside the existing helpdesk — no copy-pasting, no extra tools.
- 03
Glossary-protected replies
OpenAI translates replies back through a 200-term product glossary, keeping feature names and tone exact.
- 04
Quality loop
CSAT on translated threads is tracked separately, and low-scoring conversations are reviewed to improve the glossary.
Starts from
- Tickets in 9 languages
- Language detection
Delivers
- English view for agents
- Replies in customer's language
- CSAT tracking
The impact
The same two agents now handle tickets in nine languages, with first-response time on non-English tickets down from 26 hours to 3. Customer satisfaction on translated conversations sits at 4.7 out of 5 — indistinguishable from native English threads — and expansion into new markets no longer waits on hiring.
Questions about this automation
Do agents need a separate tool to read translated tickets?
No. Translation happens inside the existing helpdesk. Incoming tickets are language-detected and shown to agents in English with the original text kept alongside, and agents type replies in English as usual. The customer receives the answer in their own language, and nobody copies or pastes text between tools.
How does the glossary keep product terms accurate?
The glossary lists feature names, plan names and technical phrases with their approved form in each language, or a rule to leave them untranslated. OpenAI receives the glossary with every reply, so terms stay consistent across tickets. A tone setting also matches the customer's level of formality in languages where that matters.
How is translation quality checked over time?
Satisfaction scores on translated threads are tracked separately from English threads. Low-scoring conversations are reviewed, and recurring problems become new glossary entries or prompt rules. Agents can also flag a translation that reads wrong, which adds it to the same review list. Simple automations like this are usually live within days, once the first version of the glossary is drafted.