Work / AI automation / Live

Invoice and document extraction pipeline

An automation that reads supplier invoices from email, extracts the data with a vision model, checks it and posts it to the accounting system.

Problem

The accounts team typed hundreds of supplier invoices a month by hand from PDFs and scans in different formats.

Objective

Capture invoice data automatically, catch mistakes before they reach the books, and keep a person in the loop for anything uncertain.

Solution

  1. 01

    A mailbox watcher collects invoice attachments and queues them for processing.

  2. 02

    A vision-capable LLM returns structured fields — supplier, dates, line items, tax, totals — against a strict schema.

  3. 03

    Rules check the maths, match the supplier and purchase order, and flag duplicates.

  4. 04

    Clean invoices post automatically; flagged ones go to a review screen with the fields highlighted on the document.

Architecture

01
Invoice mailbox
02
Queue
03
Vision LLM extraction
04
Validation rules
05
Review UI
06
Accounting / ERP

AI workflow

01

Collect the attachment from the mailbox

02

Extract fields into a strict schema

03

Validate totals, supplier and PO match

04

Auto-post or send to human review

05

Record corrections to improve the prompts

Technology & role

PythonVision LLMRedis queuesPostgreSQLReactERP API
Our role

Process analysis, extraction pipeline, validation rules, review UI and ERP integration.

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