FINANCE

Upcoming Renewal Cost-Review Agent

Thirty days before a SaaS subscription auto-renews, an agent gathers usage and spend context, drafts a keep-renegotiate-or-cancel recommendation.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily scan for renewals within 30 days
  • ActionRead renewal records from AirtableAirtableAirtable
  • ActionQuery trailing spend and trend from BigQueryGoogle BigQueryBigQuery
  • LogicDraft recommendation and set urgency by dollar size
  • ActionSend recommendation to budget owner in SlackSlack
  • OutputRecord recommendation and decision in AirtableAirtableAirtable

What it does

Scans the subscription registry daily for renewals landing in the next 30 days. For each one, an agent pulls historical spend from BigQuery, reads the owner's notes and seat data, and drafts a recommendation: renew as-is, renegotiate, or cancel, with the reasoning and the dollar impact. The recommendation is delivered to the budget owner with a clear decision deadline.

When to use it

When auto-renewals quietly re-up at last year's seat count or a higher price and nobody revisits them in time. Use it to force a deliberate keep-or-kill decision on every renewal while there's still room to act.

How it works

  1. 1A daily schedule scans Airtable for subscriptions renewing within 30 days.
  2. 2For each upcoming renewal, the agent queries BigQuery for trailing spend and trend.
  3. 3The agent synthesizes usage, cost trend, and owner notes into a recommendation.
  4. 4A logic step sets urgency based on dollar size and days remaining.
  5. 5The recommendation and decision prompt are sent to the budget owner in Slack.
  6. 6The recommendation and any decision are recorded back in Airtable.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  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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