CUSTOMER SUPPORT
Index resolved Front threads nightly into a reply example store
Runs on a schedule to pull newly resolved Front conversations, extract the clean question-and-answer pair, embed it, and upsert it into Postgres so the auto-draft workflows…
How it runs
The automated pipeline, trigger to output.
- TriggerNightly schedule
- ActionFetch recently resolved Front threadsFront
- LogicExtract clean question/answer pair
- ActionEmbed the questionOpenAI
- OutputUpsert example into PostgresPostgres
What it does
This is the engine room behind tone-matched drafting. It keeps your example store fresh by capturing every newly resolved Front thread as a reusable question-answer pair with an embedding, so retrieval-based drafts get smarter over time without manual curation.
When to use it
Run it alongside any Front auto-draft workflow. Without a maintained example store, drafts drift toward generic; this keeps them grounded in how your team actually resolves issues this week, not last quarter.
How it works
- 1A nightly schedule triggers the indexer.
- 2It queries Front for conversations marked resolved or archived since the last run.
- 3For each thread it isolates the customer's core question and the agent's final sent reply, dropping signatures and internal comments.
- 4OpenAI generates an embedding for the question.
- 5The pair, embedding, tags, and channel are upserted into Postgres, replacing any stale version of the same thread.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 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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