FINANCE
Month-End Cash Reconciliation Investigator
On request, an agent reconciles the closing book balance against actual bank and Stripe balances, investigates every unmatched item across BigQuery transaction history.
How it runs
The automated pipeline, trigger to output.
- TriggerOperator starts month-end close from chat
- ActionRead GL and actual balances from Postgres and StripePostgres
- ActionTrace variances in BigQuery transaction historyBigQuery
- LogicClassify timing, outstanding, and fee differences
- ActionDraft reconciliation memo in NotionNotion
- OutputPost open decision items to SlackSlack
What it does
Drives the month-end cash close as an investigation. Given the period to close, the agent compares the general-ledger closing balance in Postgres against actual bank and Stripe balances, then works through each variance: tracing unmatched transactions in BigQuery history, identifying timing differences, outstanding checks, and unrecorded fees. It assembles a reconciliation memo and surfaces only the judgment calls that need a human.
When to use it
When month-end close eats days of an analyst's time tracing variances by hand. Use it to do the legwork — matching, categorizing, and documenting — so finance reviews conclusions instead of building them.
How it works
- 1An operator starts the close for a given period from chat.
- 2The agent reads the GL closing balance and actual balances from Postgres and Stripe.
- 3For each variance, it queries BigQuery transaction history to classify the cause.
- 4It reasons over timing differences, outstanding items, and unrecorded fees to build a reconciling schedule.
- 5It drafts a structured reconciliation memo in Notion with every adjustment explained.
- 6It posts open items requiring a human decision to the finance Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect StripeCustomers, subscriptions, payments.
- 3Connect BigQueryDatasets, queries, schemas.
- 4Connect NotionPages, databases, comments.
- 5Connect SlackChannels, DMs, threads, mentions.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Detect Mid-Cycle Plan Change Mischarges and Queue Credit Memos
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Draft and Send Proration Over-Billing Correction Emails
For each confirmed over-billing credit, an agent drafts a clear, customer-specific apology email explaining the proration error and the credit applied.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.