FINANCE
On-Demand RevRec Variance Lookup via Slack Command
Lets the controller request a revenue-recognition timing variance for any contract or customer on demand from Slack; the workflow queries BigQuery, has OpenAI explain the gap.
How it runs
The automated pipeline, trigger to output.
- TriggerController asks in Slack with an identifierSlack
- LogicParse contract/customer and period
- ActionQuery recognition detail for the entityBigQuery
- ActionExplain the timing varianceOpenAI
- OutputReply in the Slack threadSlack
What it does
Gives the controller a self-serve way to investigate a single contract or customer's recognition timing without writing SQL. They ask in Slack, the workflow runs the lookup, and an explained answer comes back in the same thread.
When to use it
Use it during close reviews or audit prep when someone asks "why is this customer's recognized revenue off?" and you want an answer in seconds rather than a ticket to the data team.
How it works
- 1A Slack message or slash command with a contract or customer identifier triggers the workflow.
- 2A logic step parses the identifier and period from the request.
- 3BigQuery returns recognized vs. scheduled revenue and the recognition schedule detail for that entity.
- 4OpenAI explains the timing variance, the driver, and whether it self-corrects in a future period.
- 5The explanation and figures post back as a threaded Slack reply.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Connect OpenAIModels, embeddings, files.
- 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.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.