CUSTOMER SUPPORT
Pre-Send Meaning Guard for Translated Intercom Replies
Before a translated reply leaves Intercom, it round-trips the draft and the original to verify the meaning matches, holding the reply for review if fidelity drops below threshold.
How it runs
The automated pipeline, trigger to output.
- TriggerTranslated reply drafted in IntercomIntercom
- ActionBack-translate draft to agent languageOpenAI
- ActionScore fidelity vs agent's source noteOpenAI
- LogicBranch: send if above threshold, else hold
- ActionSend reply or snooze + tag conversationIntercom
- OutputAlert lead in Slack on held repliesSlack
What it does
Adds a safety check between drafting and sending a translated reply in Intercom. It compares the agent's source-language intent against the localized draft and prevents replies that change meaning from going out to the customer.
When to use it
Use it on teams where agents write in one language and a translated version is sent to customers, and a wrong nuance (a promised refund, a denied claim) carries real cost. It turns a manual proofread into an automatic gate.
How it works
- 1A draft reply is saved on an Intercom conversation, carrying both the agent's source note and the localized draft.
- 2OpenAI back-translates the localized draft to the agent's language.
- 3OpenAI compares it against the original source note and returns a fidelity score plus specific meaning changes.
- 4A logic branch evaluates the score.
- 5On pass, the localized reply is sent via Intercom and a private note records the score.
- 6On fail, the conversation is snoozed and tagged "loc-review", with the flagged phrases posted as an internal Slack alert to the lead.
Set it up
What you configure once, before turning it on.
- 1Connect IntercomConversations, contacts, articles.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, 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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