INVOICE PROCESSING
Monthly Vendor Statement Tie-Out Against the Snowflake AP Ledger
On a monthly schedule, this pulls each vendor's latest statement from Google Drive, reconciles every invoice against the AP ledger in Snowflake.
How it runs
The automated pipeline, trigger to output.
- TriggerMonthly close schedule fires
- ActionList and read new statement files in DriveGoogle Drive
- ActionParse statements into structured invoice rowsOpenAI
- ActionQuery AP ledger entries from SnowflakeSnowflake
- LogicDiff statement vs. ledger and tag exceptions
- ActionWrite exception rows to Snowflake tableSnowflake
- OutputPost per-vendor exception digest to SlackSlack
What it does
Automates the recurring close-the-books tie-out. For every vendor statement dropped into a Drive folder, it extracts the invoice lines and compares them against the authoritative AP ledger in Snowflake. Each invoice is graded paid, open, missing-from-ledger, or amount-disagreement. Results are persisted to a Snowflake exceptions table so finance has an auditable record, and a rollup digest goes to the controller in Slack.
When to use it
Use this when your AP system of record is a data warehouse and statements arrive as files. It replaces the manual VLOOKUP ritual at month-end and gives finance a queryable history of every discrepancy.
How it works
- 1A monthly schedule fires near close.
- 2All new statement files in the designated Google Drive folder are listed and read.
- 3OpenAI normalizes each statement into structured invoice rows.
- 4Snowflake is queried for the matching vendor's ledger entries over the period.
- 5A logic step diffs statement vs. ledger and tags each row with an exception type.
- 6Exceptions are written to a Snowflake table for audit.
- 7A digest of exception counts per vendor is posted to Slack.
Set it up
What you configure once, before turning it on.
- 1Connect Google DriveDocs, sheets, slides, files.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SnowflakeWarehouses, queries, shares.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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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.
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