AI & RAG
Slack Battlecard Answerbot Grounded in Win-Loss Notes
A Slack bot that answers rep questions about a named competitor by retrieving relevant win-loss notes and approved battlecards, then drafting a grounded, cited response in-thread.
How it runs
The automated pipeline, trigger to output.
- TriggerRep mentions bot in Slack with competitor questionSlack
- ActionEmbed question and similarity-search win-loss notesPostgres
- ActionFetch matching battlecard pagesNotion
- ActionDraft grounded, cited answer with LLMOpenAI
- OutputPost cited reply in Slack threadSlack
What it does
Reps in a deal can ask, in Slack, how to handle a competitor objection. The bot retrieves the most relevant win-loss notes and approved battlecard sections, then composes a concise answer that cites exactly which past deals and cards it drew from — so no one is guessing or inventing claims.
When to use it
Use it when your sellers keep pinging product marketing or sales leadership for competitive talk tracks mid-deal, and you want consistent, source-backed answers instead of tribal knowledge. Best when win-loss notes already live in Notion and you have a vector store of them.
How it works
- 1A rep mentions the bot in a Slack channel with a competitor name and question.
- 2The bot embeds the question and runs a similarity search over indexed win-loss notes in Postgres.
- 3It pulls the matching battlecard pages from Notion for that competitor.
- 4An LLM drafts a grounded answer, refusing to speculate beyond retrieved sources.
- 5The reply posts back in-thread with citations linking each claim to its source note or card.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect NotionPages, databases, comments.
- 4Connect OpenAIModels, embeddings, files.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI & RAG workflows
RFP and security questionnaire drafter grounded in Coda
Drafts answers to inbound RFP and security questionnaire questions by retrieving approved language from your Coda hub, then files the cited draft for review before a rep sends it.
Detect Breaking API Changes from Spec Diffs and Alert Owners
Compares the new OpenAPI spec against the previous version on each GitLab merge, uses retrieval over the changelog to classify whether changes are breaking.
Grounded reply suggestions for inbound sales email
Reads inbound prospect emails, retrieves the matching answers from your Coda hub.
Coda-grounded sales answer bot with citations in Slack
Reps ask product, pricing, or competitive questions in Slack and get an answer drawn only from your Coda knowledge hub, with links to the exact docs and rows it pulled from.
On-Call Spec Answerer from Dropbox Engineering Corpus
Answers on-call questions posted in a Slack channel by retrieving the most relevant Dropbox engineering specs and replying with a grounded, source-cited answer in the thread.
Agentic Deep-Dive API Researcher for Hard Spec Questions
An agent fielded via webhook that answers multi-part API questions by iteratively searching OpenAPI specs, changelogs, and Confluence runbooks.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.