HR & RECRUITING

Agent-driven comp-exception triage and committee memo

Watches the Notion exception queue for newly flagged out-of-band employees and, for each one, the CEO agent gathers tenure, performance, and market context.

CategoryHR & Recruiting
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Notion exception card appearsNotionNotion
  • ActionAgent gathers tenure and performance contextGoogle BigQueryBigQuery
  • LogicAgent reasons on justified vs anomalous drift
  • ActionWrite recommendation memo to the Notion caseNotionNotion
  • OutputPost recommendation summary to comp committeeSlack

What it does

This workflow turns raw out-of-band flags into decision-ready cases. When a new exception lands in the Notion review queue, the agent investigates: it reads the employee's band position, pulls supporting context such as tenure and recent performance signals from the warehouse, and reasons about whether the drift looks justified or like a genuine anomaly. It then drafts a concise recommendation memo, attaches it to the Notion case, and posts a summary to the comp committee's Slack channel.

When to use it

Use this when out-of-band flags pile up faster than analysts can research them, and you want first-pass reasoning and a drafted recommendation on every case before the committee meets.

How it works

  1. 1A new Notion exception card triggers the agent.
  2. 2The agent reads the case and queries BigQuery for tenure, level history, and performance context.
  3. 3It reasons about whether the drift is justified and forms a recommendation.
  4. 4It writes the memo back onto the Notion case.
  5. 5It posts the recommendation summary to the comp committee Slack channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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.

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