INVOICE PROCESSING

Daily AP exception digest from BigQuery to Slack

On a daily schedule, summarizes all open invoice exceptions from BigQuery, groups them by reason and aging.

CategoryInvoice Processing
Enginesim
Difficultybeginner
Triggerschedule
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires before standup
  • ActionQuery all open invoice exceptions in BigQueryGoogle BigQueryBigQuery
  • ActionGroup and summarize by reason, vendor, and aging with OpenAIOpenAI
  • LogicFlag exceptions breaching their SLA age
  • OutputPost prioritized exception digest to SlackSlack

What it does

Closes the loop on exception queues that otherwise grow unbounded. Once a day it reads every unresolved invoice exception, buckets them by reason and how long they have been waiting, and delivers a single ranked summary to the AP team channel.

When to use it

Use it alongside any real-time matching flow that drops mismatches into a queue. The real-time alerts handle the moment; this digest makes sure aged exceptions actually get worked and gives leadership a daily pulse on AP health.

How it works

  1. 1A daily schedule fires each morning before standup.
  2. 2BigQuery is queried for all invoice exceptions still in an open state.
  3. 3OpenAI groups and summarizes them by reason, vendor, and aging bucket, surfacing the oldest and highest-dollar items first.
  4. 4Logic flags any exception breaching its SLA age.
  5. 5The digest posts to the AP Slack channel with counts, total dollars at risk, and the top items to clear today.

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
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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