TICKET MANAGEMENT

Auto-Tag Suspected Duplicates in Front

On each new Front conversation it scores duplicate likelihood and applies a Possible-Duplicate tag plus a private note with links.

CategoryTicket Management
Enginesim
Difficultybeginner
Triggerwebhook
Steps6
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Front conversation createdFront
  • ActionEmbed conversation with OpenAIOpenAI
  • ActionVector-search candidates in PostgresPostgreSQLPostgres
  • LogicFlag only matches above threshold
  • ActionApply Possible Duplicate tag in FrontFront
  • OutputAdd internal note with candidate linksFront

What it does

This workflow keeps everything inside Front. When a new conversation arrives, it scores whether it duplicates an open ticket and, if so, applies a Possible Duplicate tag and adds an internal note listing the likely matches. Agents see the flag directly in their inbox.

When to use it

Use it when your team lives in Front and doesn't want a separate Slack approval flow. It is the lightest-touch option: no merging, no buttons, just an in-context flag that lets agents decide and merge manually.

How it works

  1. 1A Front inbound-message webhook fires on conversation creation.
  2. 2OpenAI embeds the new conversation's subject and first message.
  3. 3The workflow vector-searches Postgres for similar open conversations and returns the top candidates.
  4. 4A threshold filter decides whether the match is strong enough to flag; weak matches stop here and the embedding is just stored.
  5. 5For a flagged conversation, the workflow applies a Possible Duplicate tag in Front.
  6. 6It adds an internal note to the conversation listing each candidate with its similarity score and a direct link for the agent to review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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