CUSTOMER SUPPORT
Language-Detecting Tone-Matched Reply Drafts in Front
Detects the language of each inbound Front message, drafts a reply in that same language with tier-appropriate formality.
How it runs
The automated pipeline, trigger to output.
- TriggerNew conversation in FrontFront
- ActionDetect message languageOpenAI
- LogicBranch on language confidence
- ActionDraft reply in detected languageOpenAI
- OutputSave draft and tag language in FrontFront
What it does
This flow reads each new Front message, detects its language, and drafts a first response written in the customer's own language at the right level of formality for their tier and locale. The detected language is recorded on the conversation so it can be routed to a native-speaking agent if needed.
When to use it
Use it when your shared inbox receives messages in several languages and English-only canned replies feel off or slow you down. Helpful for global teams that want consistent, locale-aware first responses without a separate inbox per language.
How it works
- 1A new Front conversation triggers the flow.
- 2OpenAI detects the message language and confidence.
- 3A branch flags low-confidence or unsupported languages for human routing only.
- 4OpenAI drafts a reply in the detected language using a locale-aware formality profile.
- 5The draft is saved in Front and the detected language is added as a conversation tag.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 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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