Support Customers in Their Language, Instantly

AI detects the customer's language and drafts culturally appropriate responses. Bilingual reviewers verify accuracy before delivery.

The problem

Why this matters

Hiring multilingual support staff is expensive and hard to scale. Customers writing in non-English languages either wait longer for a bilingual agent or receive awkward machine translations that damage the brand. As businesses expand globally, the gap between language demand and support capacity widens.

The solution

How MultiMail solves this

MultiMail's AI agent detects the language of inbound support emails and drafts responses in the customer's preferred language with proper cultural context and locale-specific formatting. With gated_send oversight, bilingual reviewers verify translation accuracy and cultural appropriateness before delivery.

1

Detect Language Automatically

The AI reads incoming support emails and identifies the language. It also detects cultural context clues like formality expectations, date formats, and greeting conventions.

2

Translate Context for Agent

If your support knowledge base is in English, the AI translates the customer's question into English for internal processing, then translates the response back to the customer's language.

3

Draft Response in Language

The agent drafts a culturally appropriate response in the customer's language using reply_email. The response follows local conventions for formality, salutations, and formatting.

4

Bilingual Review

With gated_send, a bilingual reviewer verifies translation accuracy, cultural appropriateness, and technical correctness before the response reaches the customer.

Try it

Try it with your agent

Pick your platform, copy the prompt, and paste it to your AI agent — it sets up MultiMail and builds the whole flow. Nothing to fill in.

1. Get MultiMail ready: read https://multimail.dev/llms.txt, connect the MCP server, create a free inbox, and set up a verified sender. 2. In Zendesk, use ticket triggers or webhooks to detect new or updated email tickets where the requester language is non-English, using Zendesk ticket fields, tags, requester locale, or message content as the signal. 3. For each qualifying ticket, identify the customer's language and locale, read the full conversation history, draft a support reply in that language, preserve the brand voice, and adapt date, currency, tone, greeting, and formality to the customer's region. 4. Compose the reply in MultiMail and run it in gated_send mode so a bilingual reviewer must approve translation accuracy, cultural appropriateness, and policy correctness before delivery. 5. Ask me only for Zendesk access, MultiMail credentials, the verified sending domain, brand voice guidance, supported languages, escalation rules, and reviewer assignments before going live.
Benefits

What you get

Support Any Language Instantly

AI responds in the customer's language within minutes, eliminating the wait for a bilingual agent to become available.

Cultural Awareness

AI adapts formality level, greeting conventions, and formatting to match cultural expectations — not just word-for-word translation.

Bilingual Quality Control

Gated send ensures a bilingual reviewer verifies translation quality before customers see the response, catching nuances that AI translation might miss.

Scale Global Support Affordably

Support customers in 20+ languages without hiring native speakers for each one. One bilingual reviewer can handle multiple languages more efficiently.

Oversight

Recommended oversight mode

Recommended
gated_send
AI translation can miss cultural nuances, idioms, and technical terminology in other languages. Gated send ensures a bilingual reviewer catches translation errors before customers receive responses that could be confusing or culturally inappropriate.
FAQ

Common questions

How many languages does this support?
MultiMail handles the email infrastructure in any language — there are no character set or encoding limitations. The language detection and translation quality depends on your AI model. Modern LLMs support 50+ languages with varying quality levels.
What if we don't have bilingual reviewers for every language?
Focus bilingual review on your highest-volume non-English languages. For rare languages, you can start with monitored mode to build confidence in the AI's translation quality before relaxing to less frequent review.
How does the AI handle technical terms?
You can provide a glossary of technical terms and their approved translations in each language. The AI uses this glossary to ensure product names, feature terms, and technical concepts are translated consistently.
Can I detect the preferred language for returning customers?
Yes. Save contacts with their detected language preference using add_contact, then look them up with search_contacts. On subsequent interactions, the AI can immediately draft in the customer's known language preference without needing to re-detect.
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