AI & RAG
Contract Clause Q&A in Slack, Grounded in Confluence Policy Library
Lets a teammate ask a contract or policy question in Slack and replies with a grounded answer plus a citation back to the exact source paragraph in your versioned Confluence…
How it runs
The automated pipeline, trigger to output.
- TriggerTeammate asks a policy question via Slack commandSlack
- ActionEmbed question and retrieve top policy chunks from Supabase pgvectorSupabase
- LogicGate on retrieval relevance; flag weak or no-match results
- ActionGenerate grounded answer with clause snippet and Confluence citationOpenAI
- OutputPost threaded reply with answer and source paragraph linkSlack
What it does
Turns your Confluence policy space into an answerable knowledge base. A user types a question in a Slack channel (e.g. "What's our standard liability cap for SaaS deals?") and gets back a concise answer that quotes the governing clause and links to the precise Confluence paragraph and page version it came from.
When to use it
Use it when legal, sales, or procurement teammates repeatedly ask the same contract and policy questions and you want answers that are auditable, not hallucinated. Best when your authoritative policies already live in a Confluence space and you need every reply to cite its source.
How it works
- 1A Slack slash command or mention fires with the user's question.
- 2The flow embeds the question with OpenAI and retrieves the top-matching policy chunks from a Supabase pgvector store synced from Confluence.
- 3A relevance gate checks whether retrieved chunks actually cover the question; weak matches are flagged.
- 4OpenAI generates a grounded answer constrained to the retrieved text, attaching the clause snippet, Confluence page title, version, and anchor link.
- 5The answer and citation post back as a threaded Slack reply.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect SupabaseTables, auth, storage, edge functions.
- 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.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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