FINANCE

On-demand CEO briefing on billing vs. recognition divergence

On request in chat, the CEO agent queries BigQuery for the worst billing-versus-recognition divergences, investigates the underlying contracts.

CategoryFinance
Enginepaperclip
Difficultyadvanced
Triggerchat
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerChat request to CEO for deferral briefing
  • ActionQuery top divergences in scope from BigQueryGoogle BigQueryBigQuery
  • LogicInvestigate each contract's schedule break
  • ActionCompose ranked briefing with OpenAIOpenAI
  • OutputReturn briefing in chat, offer to draft entries

What it does

When the Chairman asks about deferral health, the CEO agent pulls the current billing-versus-recognition divergence picture from BigQuery, digs into the specific contracts driving it, and explains what's wrong and what to do about it. Unlike the scheduled monitors, this is conversational and exploratory — you can ask follow-ups, scope to a segment, or request the journal entries to fix it.

When to use it

Reach for it when you don't want to wait for the nightly job — board prep, an ad-hoc auditor question, or a gut-check before signing the close. It turns the raw schedule data into a decision-ready answer on demand.

How it works

  1. 1A chat message to the CEO starts the briefing.
  2. 2The agent runs a BigQuery query for the largest billing-vs-recognition divergences in the requested scope.
  3. 3It reasons over each top contract — billing cadence, recognition method, and where the schedule broke.
  4. 4It uses OpenAI to compose a ranked briefing with a plain-English cause and a suggested deferral correction per contract.
  5. 5The agent returns the briefing in chat and offers to draft the adjusting entries.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    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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