AI AGENTS
Draft SOC2 questionnaire answers from your policy library
When a vendor security questionnaire is dropped into a Drive folder, an agent reads each question, retrieves the matching policy evidence from Confluence.
How it runs
The automated pipeline, trigger to output.
- TriggerNew questionnaire file in Drive folderGoogle Drive
- ActionParse file into discrete questions
- ActionRetrieve matching policy from ConfluenceConfluence
- ActionDraft grounded answer per question, flag gaps
- OutputPost drafted Q&A to Slack for reviewSlack
What it does
Turns an incoming vendor SOC2 questionnaire into a fully drafted set of answers, each one grounded in your actual security policies rather than invented. A reviewer gets a clean Slack thread with every question, the proposed answer, and a link to the source policy.
When to use it
Use this when prospects or customers regularly send security questionnaires (SIG, CAIQ, custom spreadsheets) and your team copies answers by hand from a policy wiki. Best for teams that want a human to approve before anything is sent.
How it works
- 1A new questionnaire file landing in a watched Google Drive folder triggers the run.
- 2The agent parses the file into a list of discrete questions.
- 3For each question it searches your Confluence security space for the relevant policy or control narrative.
- 4It drafts an answer constrained to the retrieved text, flagging any question with no supporting policy as a gap.
- 5The drafted Q&A set, with source links, is posted to a Slack review channel for sign-off.
Set it up
What you configure once, before turning it on.
- 1Connect Google DriveDocs, sheets, slides, files.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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.
More AI Agents workflows
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Datadog Bill Spike Attribution Agent
When a daily Datadog cost check detects a spend jump, an agent attributes the increase to the specific services and metric types driving it and posts a ranked breakdown to Slack.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
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.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.