Tax Document AI

The problem

Small businesses drown in receipts, invoices, and PDF statements. Manual categorization against a German chart of accounts (SKR03 / SKR04) takes hours every month. Generic OCR services dump raw text, forcing the accountant to re-type line items anyway.

What I built

A document intake pipeline that accepts PDFs, images, and email attachments, runs layout-aware OCR, uses an LLM to extract structured line items, validates against business rules, categorizes to the chart of accounts, and exports an accountant-ready batch — DATEV-compatible CSV or pre-filled booking PDFs.

Architecture

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  Ingestion

  Web upload, email attachment, or folder watcher; MIME detection and virus scan

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  OCR layer

  Tesseract for simple receipts, PaddleOCR for complex multi-column invoices, German-language models

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  LLM extraction

  Ollama-hosted model with structured-output prompts to emit JSON line items (date, counterparty, VAT rate, net/gross, account hint)

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  Validation

  Deterministic rules for VAT plausibility, duplicate detection, date-range checks

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  Storage

  PostgreSQL with full-text search across extracted documents

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  Export

  DATEV CSV, accountant-ready PDF summary, or direct push to a bookkeeping system

Tech stack