FINANCE
Generate a month-end deferred-revenue close narrative
At month-end, pulls the deferred-revenue rollforward from BigQuery, has an LLM write a plain-English narrative explaining the movement and the largest divergence drivers.
How it runs
The automated pipeline, trigger to output.
- TriggerMonth-end schedule after ledger lock
- ActionPull deferred-revenue rollforward from BigQueryBigQuery
- ActionDraft close narrative with OpenAIOpenAI
- LogicFlag if divergence exceeds materiality
- OutputDeliver memo to controller in SlackSlack
What it does
This workflow produces the written explanation a controller needs at close: it reads the deferred-revenue rollforward (opening, additions, recognized, ending) from BigQuery and uses an LLM to draft a narrative covering total movement, the contracts driving recognition this period, and any schedules that diverged from plan. The outcome is a review-ready memo instead of a blank text box.
When to use it
Run it on the last business day of the period when you need the deferred-revenue flux commentary for the close package or audit workpapers, and you want a consistent, sourced first draft every month.
How it works
- 1A month-end schedule triggers after the ledger is locked.
- 2A BigQuery action returns the rollforward plus the top divergence contracts for the period.
- 3An OpenAI step turns the figures into a structured narrative with the numbers cited inline.
- 4A logic step appends a flag if any divergence exceeds the materiality threshold so the controller can't miss it.
- 5The finished memo is delivered to Slack tagging the controller for review.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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