CUSTOMER SUPPORT
Knowledge-Base-Grounded Reply Drafts for Front
Pulls the relevant help-center article for an incoming Front question and drafts a reply grounded in that article, linking the source so agents send accurate.
How it runs
The automated pipeline, trigger to output.
- TriggerNew question in Front inboxFront
- ActionSearch knowledge base for relevant articleNotion
- LogicBranch on article match confidence
- ActionDraft answer grounded in the articleOpenAI
- OutputSave grounded draft to FrontFront
What it does
When a customer asks a how-to or product question in Front, this flow finds the most relevant knowledge-base article, drafts a reply that answers using only that article's content, and attaches the source link. Agents get a factual, citable draft rather than an AI guess, cutting both reply time and the risk of confidently wrong answers.
When to use it
Use it for support inboxes dominated by repetitive product and how-to questions where answers already exist in your help center. Best when accuracy matters and you want every reply tied to a maintained source of truth.
How it works
- 1A new Front conversation triggers the flow.
- 2The question text is used to search the Notion-based knowledge base for the closest article.
- 3A branch routes questions with no confident article match to a plain acknowledgment draft instead.
- 4OpenAI drafts an answer grounded strictly in the retrieved article and includes its link.
- 5The grounded draft is saved to the Front conversation for agent review.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 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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