TICKET MANAGEMENT
Front cross-channel duplicate collapser for email and chat reports
Scans newly received Front conversations across email and chat, finds when the same customer reported the same issue twice through different channels.
How it runs
The automated pipeline, trigger to output.
- TriggerNew inbound Front conversationFront
- ActionEmbed conversation textHugging Face
- ActionLoad contact's open conversationsFront
- LogicSame issue across channels?
- ActionMerge into canonical conversation + noteFront
- OutputLog merge decision for auditPostgres
What it does
Customers often email support and then open a live chat about the same problem minutes later, splintering the context across two Front conversations. This workflow recognizes the overlap by comparing the new conversation against the requester's recent threads and collapses the duplicate into a single canonical conversation, preserving both channels' history.
When to use it
When your team uses Front for multiple inboxes (email, chat, SMS) and the same person frequently reaches out twice. It keeps one timeline per issue so agents stop replying in parallel.
How it works
- 1A new inbound Front conversation triggers the flow.
- 2The conversation text is embedded via Hugging Face.
- 3Other open conversations from the same contact are loaded from Front and compared.
- 4A branch decides if the closest match is the same underlying issue.
- 5If so, the newer conversation is merged into the older canonical one and an internal note records the link.
- 6The merge decision and score are logged to Postgres for audit and tuning.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 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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