Datamolino vs invoice2data

Datamolino captures supplier invoices, receipts and bank statements, applies saved coding rules, routes invoices for approval and exports checked data to accounting software. Documents can arrive by email, web upload or mobile receipt photo, and ordered PDF batches can be split into individual invoices. Approval workflows are configurable, with decisions kept alongside each invoice. Line-item capture and editing are available on selected plans, including account and tax-code assignment to individual lines. Connections include Xero, QuickBooks Online and FreeAgent, specialist connections and a Capture API for uploading documents, receiving processing webhooks and retrieving structured data. Bank statement PDFs are converted to transaction data and charged per page. Start costs £17 a month excluding VAT and includes 100 bills and receipts per month for one company, with unlimited users; Build is £29 a month, LAUNCH 39.00 GBP, Grow 55.00 GBP, SCALE 135.00 GBP and EXPAND 500.00 GBP. A 14-day trial is available. The mobile app captures documents for Purchases only; sales invoices, bank statements, coding and exports are handled in the web app. Datamolino says stored files are encrypted with AES-256 and customer data is hosted with Amazon Web Services in the European Union.

invoice2data is a command-line tool and Python library that extracts structured information from PDF invoices for accounting workflows. It reads invoice text using selectable backends, including pdfium, pdftotext, pdfminer, pdfplumber, and OCR tools. YAML or JSON templates identify fields and can specify custom fields and multiple regular expressions for each one. The command-line tool can export extracted results as CSV, JSON, or XML and rename PDFs based on their contents. Optional plugins support invoice line items and tables, with Camelot available for advanced table parsing. Optional AI features can help draft templates or extract fields when template matching fails. AI does not run unless a provider is configured; the default mock provider has no network access. Listed providers include OpenAI, DeepSeek, Mistral, Gemini, and Ollama, which can run locally. Local OCR options include docTR and PaddleOCR. The project is free under the MIT License, with pip and conda installation routes. It runs on Linux, macOS, Windows, and self-hosted systems.