FINANCE

Runway Impact Check on Large Spend Approval

When a large spend or contract is submitted for approval via webhook, recomputes projected runway with that commitment included and routes an approve-or-hold recommendation…

CategoryFinance
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSpend-approval submitted via webhookHTTP webhook
  • ActionPull baseline cash and burn from BigQueryGoogle BigQueryBigQuery
  • LogicRecompute projected runway with commitment
  • LogicCompare projected runway to safety floor
  • OutputPost approve-or-hold recommendation to Slack threadSlack

What it does

Turns runway from a backward-looking metric into a forward-looking decision input. When someone submits a large purchase or recurring contract for approval, it recomputes runway as if the commitment were already live and recommends whether the spend keeps the company above its safety floor.

When to use it

Use it when approvers green-light big spend without seeing the cash impact. This puts the projected post-commitment runway directly in front of the decision-maker before they click approve.

How it works

  1. 1A spend-approval submission arrives by webhook with amount, cadence, and category.
  2. 2Pulls current cash, burn, and revenue inputs from BigQuery to establish the baseline.
  3. 3A logic step recomputes projected runway with the new recurring or one-time commitment folded into burn.
  4. 4Compares the projected runway against the configured safety floor to produce an approve or hold recommendation.
  5. 5Posts the baseline runway, projected runway, and the recommendation into the Slack approval thread for the approver to act on.

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
    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.

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