CUSTOMER SUPPORT
Detect ticket language and route to the right Front queue
When a new conversation lands in Front, detects its language with a Hugging Face classifier, translates the body to English for agents.
How it runs
The automated pipeline, trigger to output.
- TriggerNew Front conversation receivedFront
- ActionDetect language via Hugging Face classifierHugging Face
- LogicBranch on confidence and non-English language
- ActionTranslate body to English via Hugging FaceHugging Face
- ActionPost translation as private commentFront
- OutputAssign to language-matched inbox and tagFront
What it does
Every inbound Front conversation gets its language detected automatically. The workflow runs a Hugging Face language-identification model over the message body, writes both the detected language and an English translation back to the conversation as a private comment, and moves the ticket into the inbox staffed by agents who speak that language.
When to use it
You run a single shared support inbox but have agents grouped by language skill (Spanish, German, Japanese, etc.). Without this, multilingual tickets sit unread until someone who can read them stumbles in. Use it to cut first-response time on non-English tickets.
How it works
- 1A new Front conversation triggers the flow.
- 2The message body is sent to a Hugging Face language-detection model, returning an ISO language code and confidence.
- 3A branch checks confidence: high-confidence non-English routes onward; low-confidence or English stays in the default queue.
- 4The body is translated to English via a Hugging Face translation model.
- 5The translation is posted as a private comment on the conversation.
- 6The conversation is assigned to the inbox mapped to the detected language and tagged with that language.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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