CUSTOMER SUPPORT
Translated Reply Escalation on Semantic Gap in Front
When a translated reply is sent in Front, it back-translates the sent message, measures meaning loss against the agent's original.
How it runs
The automated pipeline, trigger to output.
- TriggerTranslated reply sent in FrontFront
- ActionBack-translate sent reply to agent languageOpenAI
- ActionScore meaning loss + classify severityOpenAI
- LogicRoute by severity tier
- ActionCreate Linear correction issue on severeLinear
- OutputEscalate to lead in SlackSlack
What it does
Provides a post-send safety net for localized customer replies in Front. It catches replies that already went out with a meaning gap and routes the worst ones into an actionable correction workflow before the customer is misled further.
When to use it
Use it when your team sends translated replies at volume and you want a tracked record of localization failures rather than a one-off Slack ping. Pairs well with a same-conversation follow-up correction policy.
How it works
- 1A reply is sent on a Front conversation that carries an agent source draft and a localized version.
- 2OpenAI back-translates the sent localized reply to the agent's language.
- 3OpenAI scores meaning loss against the original and classifies severity (minor, moderate, severe).
- 4A logic branch routes by severity.
- 5On severe, a Linear issue is created with the conversation link, the diff, and the fidelity score for a follow-up correction.
- 6A Slack escalation notifies the on-shift lead; minor and moderate gaps are logged as a Front comment only.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect LinearIssues, projects, cycles, triage.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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