Affinda Invoice Extractor vs invoice2data
Affinda Invoice Extractor
affinda.cominvoice2data
github.comSide by side
| Figure | Affinda Invoice Extractor | invoice2data |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · Invoice Processing Software | 8.7 (#5) | 7.8 (#16) |
| Extraction | The invoice platform can capture standard invoice fields, line items, totals, tax, payment details, and custom fields. | It extracts PDF text through selectable backends including pdfium, pdftotext, pdfminer, pdfplumber, and OCR tools. |
| Purpose | Affinda Extract automates invoice processing by splitting and classifying documents, extracting and validating data, and routing structured output to business systems. | invoice2data is a command-line tool and Python library that extracts structured information from PDF invoices for accounting workflows. |
| Security | Affinda states it is ISO 27001:2022 certified, SOC 2 Type 2 and GDPR compliant, encrypts data in transit and at rest, and offers multi-factor authentication. | The repository's GitHub security page says no SECURITY.md policy is set up and no security advisories are published. |
| Support | Standard platform support is included in standard usage; priority support and a dedicated Customer Success Manager are listed as paid add-ons. | The repository invites issues and pull requests, and links to a contributor guide; it does not describe a paid support plan on the pages reviewed. |
Plans
Affinda Invoice Extractor
- TrialFree
- Flexible usagePrice not published
- Platform add-onsPriced on request
- Predictable scalePrice not published
In their own words
Affinda Invoice Extractor
Affinda Invoice Extractor has no write-up on Specifiction yet; its figures are above.
invoice2data
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.