AI & RAG
On-Demand Objection Battlecard Builder
Given a competitor or objection topic, an agent reads across the won/lost transcript corpus in Dropbox and assembles a complete battlecard — proven rebuttals, traps to avoid.
How it runs
The automated pipeline, trigger to output.
- TriggerRep submits topic or competitor via chat
- ActionRetrieve matching snippets from Notion corpusNotion
- ActionRead full source transcripts in Dropbox for contextDropbox
- LogicSeparate winning rebuttals from losing patterns
- ActionCompose structured battlecard with OpenAIOpenAI
- OutputPublish battlecard as Notion page and return linkNotion
What it does
This is an agent-driven workflow that builds a full battlecard on demand rather than returning a single snippet. You give it a topic such as "replatforming risk" or a competitor name, and the agent retrieves every relevant moment across won and lost transcripts, reasons over the patterns, and composes a structured battlecard: the objection, the rebuttals that won, the phrasing that lost, and verbatim quotes with source links.
When to use it
Use it when enablement needs a durable, shareable artifact for a recurring objection or a specific competitor, not a one-off live answer. It is the deepest synthesis surface over the same corpus.
How it works
- 1A rep or manager submits a topic or competitor via a chat request.
- 2The agent embeds the topic and retrieves all matching snippets from the Notion-indexed corpus.
- 3The agent reads the source transcripts in Dropbox for full context around each match.
- 4It reasons over won versus lost patterns to separate effective rebuttals from failed ones.
- 5It drafts a structured battlecard with rebuttals, anti-patterns, and cited quotes.
- 6The finished battlecard is published as a formatted Notion page and the link is returned to the requester.
Set it up
What you configure once, before turning it on.
- 1Connect OpenAIModels, embeddings, files.
- 2Connect NotionPages, databases, comments.
- 3Connect DropboxFiles and folders.
- 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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