FINANCE

Re-evaluate deferral schedules on contract modifications

When a contract is amended, recomputes the remaining recognition schedule in BigQuery, diffs it against the prior schedule.

CategoryFinance
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook: contract modifiedHTTP webhook
  • ActionRecompute remaining schedule in BigQueryGoogle BigQueryBigQuery
  • LogicDiff vs. prior schedule, classify materiality
  • ActionRoute material changes to Slack for sign-offSlack
  • OutputSync approved schedule to PostgresPostgreSQLPostgres

What it does

Contract amendments — upsells, renewals, downgrades, early terminations — change how remaining revenue should recognize. This workflow catches the modification event, rebuilds the go-forward recognition schedule, and compares it to the schedule it replaces. The outcome is that mid-term changes get reflected in deferred revenue immediately, with a human review step for anything material.

When to use it

Use it when contract changes are frequent enough that re-spreading by hand causes drift between billing and recognition. It keeps the schedule current without finance re-deriving every amendment from scratch.

How it works

  1. 1A webhook fires when a contract is modified in the CLM or CRM.
  2. 2A BigQuery action recomputes the remaining recognition rows from the amended terms and the already-recognized balance.
  3. 3A logic step diffs the new schedule against the prior one and classifies the change as immaterial or needs-review.
  4. 4Needs-review changes post to Slack with old-vs-new amounts for sign-off.
  5. 5A Postgres action writes the approved schedule so billing stays aligned.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect PostgresAny Postgres URL — query, write, migrate.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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