AI AGENTS
SOC2 Audit-Window Evidence Package Assembler
On demand from a webhook, an agent gathers all control evidence for a named audit period from Airtable and GitHub, assembles a structured evidence package in Google Drive.
How it runs
The automated pipeline, trigger to output.
- TriggerWebhook supplies audit period datesHTTP webhook
- ActionQuery evidence records for the windowAirtable
- ActionAttach point-in-time GitHub PR historyGitHub
- LogicCheck each control for coverage gaps
- ActionBuild per-control folders and uploadGoogle Drive
- OutputSend audit lead the Drive link and gap listSlack
What it does
Collapses the worst week of every SOC2 audit into a single run. Given an audit period, it pulls the relevant evidence records, organizes them by Trust Services Criteria, and produces an auditor-ready folder so the team isn't hand-collecting screenshots the night before fieldwork.
When to use it
Trigger it when fieldwork is scheduled or when the auditor sends an evidence request list. It complements the collectors that gather evidence continuously by packaging that evidence into a deliverable.
How it works
- 1A webhook trigger supplies the audit period start and end dates.
- 2An agent queries Airtable for every evidence record dated within the window and groups it by control family.
- 3It calls GitHub to attach point-in-time artifacts like merged-PR review history for the window.
- 4A logic step checks each required control for at least one evidence item and flags coverage gaps.
- 5It creates a dated, per-control folder structure in Google Drive and uploads the artifacts.
- 6It messages the audit lead in Slack with the Drive link and the list of any controls still missing evidence.
Set it up
What you configure once, before turning it on.
- 1Connect AirtableBases, tables, views, automations.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect Google DriveDocs, sheets, slides, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Connect HTTP webhookTrigger any URL on agent actions.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Observability Cost Allocation Report
Monthly, an agent pulls Datadog and Honeycomb usage, allocates spend to teams and services by tags, writes the breakdown to Snowflake, and posts a chargeback summary to Slack.
Vendor Shortlist Matrix from a Buying Brief
An agent reads a buying brief, researches candidate vendors across the live web, and builds a scored comparison matrix in Coda ranking each vendor against your stated criteria.
Split oversized Linear epics into estimated child issues
An agent scans newly created Linear epics, breaks each one above a size threshold into discrete child issues with point estimates and acceptance criteria.
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.
Buying Brief Email to Shortlist Doc in Drive
When a buying brief arrives by email, an agent researches the market and produces a polished narrative shortlist document in Google Drive, then replies to the sender with the link.
Zoom Demo Low-Score Objection Escalation to Manager
Scores how well a rep handled objections in each Zoom demo, and only when the handling score falls below a threshold does it create a coaching task in ClickUp and alert the rep's…
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.