AI AGENTS
Pre-board KPI anomaly pre-read alert
Two days before each board meeting, scans warehouse KPIs for anomalies against forecast and posts a ranked pre-read of what the board will ask about to Slack.
How it runs
The automated pipeline, trigger to output.
- TriggerCalendar event: 2 days before board meetingGoogle Calendar
- ActionPull actuals vs forecast for all KPIsSnowflake
- LogicFilter to out-of-tolerance metrics, rank by severity
- ActionWrite explanation + talking point per anomalyOpenAI
- OutputPost ranked pre-read to leadership SlackSlack
What it does
Generates the pre-read that gets executives ahead of the hard questions. It compares this period's KPIs against forecast and trailing trend, isolates the metrics that deviate beyond tolerance, and writes a short ranked brief on each anomaly with a probable explanation so the team can prepare answers before they're in the room.
When to use it
Use it when board meetings get derailed by a metric nobody pre-explained, and you want a deviation-driven heads-up rather than a full deck. Triggered off a calendar event so it always lands ahead of the meeting.
How it works
- 1A Google Calendar event two days before the board meeting triggers the run.
- 2Snowflake returns actuals versus forecast for every tracked KPI.
- 3A logic step keeps only metrics deviating past their tolerance band and ranks them by severity.
- 4OpenAI writes a one-paragraph explanation and suggested talking point per anomaly.
- 5The ranked pre-read is posted to the leadership Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect Google CalendarEvents, attendees, availability.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 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 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.
