AI & RAG

Slack Evidence Lookup with Citations for Compliance Teams

Lets staff ask compliance evidence questions from a Slack slash command or mention and replies in-thread with a grounded answer plus clickable links to the exact source clauses.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack slash command or mention with a questionSlack
  • ActionEmbed question and retrieve clauses from pgvectorPostgreSQLPostgres
  • LogicBranch on retrieval confidence: answer vs evidence-gap
  • ActionGenerate grounded answer with citation markersOpenAI
  • OutputReply in-thread with citations or post gap alert to GRC channelSlack

What it does

Turns the compliance evidence corpus into a self-serve Slack tool. A team member asks a question in Slack; the bot retrieves the supporting clauses, drafts an answer constrained to that evidence, and posts it back in-thread with citation links to the source documents. When no clause clears the confidence bar, it flags the gap to a GRC review channel so an owner can fill it.

When to use it

When sales engineers, security reviewers, or new hires repeatedly ask 'do we have a control for X?' and you want answered-with-receipts responses in Slack instead of pinging the compliance lead.

How it works

  1. 1A Slack slash command or app mention triggers the flow with the user's question.
  2. 2The question is embedded and matched against corpus clauses in pgvector.
  3. 3A confidence branch decides: answer if supported, else route to the gap path.
  4. 4OpenAI drafts a grounded answer with inline citation markers.
  5. 5The answer with source-clause links posts back to the originating Slack thread; unsupported questions post an evidence-gap alert to the GRC channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SlackChannels, DMs, threads, mentions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.