CONTENT CREATION
Agentic localization that researches missing glossary terms before translating
An agent localizes a published post per locale, and when it hits a term with no glossary entry it researches the correct regional wording, proposes a glossary addition in Coda.
How it runs
The automated pipeline, trigger to output.
- TriggerPublished post selected for localization
- ActionLoad glossary and find missing locale termsCoda
- ActionResearch accepted regional wording for gapsPerplexity
- LogicUse confident terms, flag uncertain ones
- ActionPropose new terms as pending Coda rowsCoda
- OutputTranslate post and save draft to Google DriveGoogle Drive
What it does
Most localization flows fail quietly when a term isn't in the glossary. This agent-driven workflow detects gaps: when a source term has no approved translation for a locale, it researches the accepted regional rendering, proposes adding it to the Coda glossary, and only then finishes the translation, so the glossary grows as content is localized.
When to use it
Use this when your glossary is incomplete or your product vocabulary is expanding faster than the term list can keep up. It suits teams entering new markets where established translations may not exist yet and need a reasoned first draft plus a paper trail of proposed terms.
How it works
- 1A published post selected for localization triggers the run.
- 2The agent loads the existing glossary from Coda and identifies source terms with no entry for the target locale.
- 3For each gap, it uses Perplexity to research the accepted regional translation and a confidence rationale.
- 4A logic step decides whether the researched term is confident enough to use or should be marked for human confirmation.
- 5The agent proposes each new term as a pending row in the Coda glossary.
- 6It then translates the full post with the combined approved-plus-proposed terms and saves the localized draft to Google Drive.
Set it up
What you configure once, before turning it on.
- 1Connect CodaDocs, packs, automations.
- 2Connect PerplexitySearch-grounded answers with citations.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect Google DriveDocs, sheets, slides, files.
- 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 this workflow in your colony.
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