Anmol Baranwal

Posted on Sep 13

Top 11 Document Parsing AI Tools for developers in 2025

#ai #tooling #beginners #webdev

Working with documents can get messy. You have PDFs, scanned files, forms and all kinds of formats.

But now there are smart tools that can read and understand them for you. They can read, extract and organize data with almost no manual effort.

Today, we will go over the top 11 Document parsing AI tools that developers should know about. What they are good at, how they work and when to use them.

You will find a detailed comparison table at the end.

1. Invofox - Document parsing for invoices, receipts, payslips, bank statements, loans & mortgages with multi-language support.

Invofox makes it super easy to extract data from invoices, receipts, payslips, bank statements, loan/mortgage files and custom document types like bills. No templates are needed at all. They turn messy, unstructured documents into clean, predictable JSON.

As per the official website, you can process 1k+ documents under 30 seconds. I was researching how companies use Invofox (for parsing docs):

Payroll solutions use it to parse payslips during customer onboarding. They collect 12–24 months of payslips, structure the data and ingest it (to automate a large part of the process).
Fintech companies use it to process large loan and mortgage files. Invofox splits the files (often hundreds of pages), classifies each document, runs OCR, structures the data, removes duplicates and validates automatically (fully automating the workflow).

They use advanced AI models with proprietary algorithms that verify and autocomplete your data. Check API Docs.

Features:

No-code setup for quick document automation
No tuning, no prompt hacking required
Handles multiple layouts and languages
Model-agnostic, handled under the hood
Built-in analytics and quality tracking
Built-in validation, autocomplete & document-level confidence

Here is the demo video!

I have compared it with GPT-4o and found the results impressive.

2. Google Document AI - cloud-scale document understanding with pre-trained models.

Document AI helps developers create high-accuracy processors to extract, classify and split documents. Backed by Google's models, this option is ideal for large-scale document processing, offering solid support for both structured and unstructured documents.

It's cloud-native and highly scalable with pre-trained and custom models. Excels in enterprise and developer use. Here is the demo video!

Features:

Pre-trained models for invoices, contracts, forms and IDs
High accuracy OCR and layout detection
Part of Google Cloud, supports batch processing at scale
Easily integrates with other GCP tools like BigQuery and Vertex AI

You can try the demo on the landing page with samples.

You can also check out the repo for Sample applications and demos that demonstrate how to analyze, classify and search documents using Google Cloud Document AI.

3. Amazon Textract - deep learning based OCR with table and form extraction.

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, layout elements and data from scanned documents. It goes beyond simple optical character recognition (OCR) to identify, understand and extract specific data from documents.

You can securely automate data processing with data privacy, encryption, and compliance standards. PayTM uses this service, so it has a huge credibility.

Features:

Extracts structured data from tables and forms
Integrates with AWS Lambda, S3 and other AWS services
Scalable, serverless OCR processing
Good support for scanned and handwritten documents

Here is the demo video!

4. ABBYY FlexiCapture - enterprise-grade document automation with advanced rules and scripting.

FlexiCapture brings together the best artificial intelligence (AI), natural language processing (NLP), machine learning (ML), and advanced recognition capabilities into a single, enterprise-scale document automation platform to transform all the data from your business documents.

It's available in the cloud, on-premises or as an SDK. It works in three simple steps:

⚡ Automatically processes all types of documents from files and scanners in a single flow, including office documents and image formats, email attachments and message bodies.

⚡ Uses neural networks that can now automatically sort documents by type like invoices, contracts, or IDs and even by custom categories, such as invoices from different vendors. They learn quickly from examples and act as smart auto-classifiers based on text and layout.

⚡ Document content and data are automatically extracted and validated. It uses advanced OCR/ICR/OMR, handwriting, barcode recognition and checks the data against databases with built-in rules for accuracy.

Here is the demo video!

Features:

Rule-based and AI-powered document classification
Supports complex workflows and custom data validation
Great for enterprise-scale automation
Integration with ERP/CRM systems like SAP, Salesforce

5. Docsumo - clean data tables from unstructured docs in seconds.

An intelligent Document AI platform that helps businesses extract clean, structured data from unstructured documents like invoices, bank statements, utility bills and more in just seconds. With advanced OCR, table detection, and smart validation rules, Docsumo automates the entire document workflow, drastically reducing manual effort and human errors.

It supports multiple formats (PDF, PNG, JPG, Excel, emails) and integrates easily with existing systems via powerful APIs.

Plus, it’s secure (SOC2, HIPAA, GDPR compliant) and supports pre-trained or custom-trained models to meet your specific use cases. Here is the demo video!

Features:

Auto-classifies and extracts data from invoices, bank statements, etc.
Built-in document validation and correction interface
Scalable cloud-native architecture

6. Nanonets - Train custom document models easily.

Another AI document automation platform is designed to extract structured data from unstructured sources like invoices, receipts, emails and more.

With advanced AI extractors and no reliance on fixed templates, it provides rapid setup (2–3x faster than industry standards). The platform integrates easily with CRMs, ERPs, and storage systems, and supports real-time validation, approval flows and end-to-end automation.

Here is the demo video!

Features:

Train models on your own document types
Drag-and-drop UI or API-based training
Real-time data extraction and webhook integration
No-code model deployment in minutes

7. Parsio - email and document parser for structured data extraction.

Document and email parser that transforms unstructured data like PDFs, emails and attachments, into structured formats with speed and precision.

With its new GPT-powered Airparser and Mistral OCR, Parsio delivers advanced document understanding in multiple languages and formats. Automate data extraction, formatting, and export to tools like Google Sheets, Slack, QuickBooks and cloud storage.

Here is the demo video!

Features:

Parses PDFs, HTML emails and attachments
Extracts text into structured formats like JSON or CSV
Automation-friendly: webhooks and Zapier integrations
No-code rule setup for repeated formats

8. Rossom - Intelligent, template-free document processing.

It's an AI-powered platform that takes document processing completely off your plate. It reads, understands and extracts data from documents like invoices, purchase orders and bills of lading, and then actually does something with that data.

You can validate it, send emails, request approvals, update your ERP (like SAP, NetSuite, Coupa) and more.

You can ingest documents via email, scanners, shared drives, PEPPOL and let Rossum’s AI agents handle everything end-to-end.

Features:

Built-in LLM trained on millions of transactional docs
Pre-trained AI that learns from user feedback
Designed for high-volume, low-code environments
Powerful email-to-API pipeline for automation
Supports multi-document and multi-language processing (276 languages)

9. Affinda - AI parsing for resumes, invoices, business docs.

Automate document processing without the complexity. The platform uses deep learning, NLP, and computer vision to read and extract data from any document, across 50+ languages and works out of the box for tons of use cases.

Features:

Handles 40+ document types (and counting)
No-code setup with easy integration into your current tools
Specializes in recruitment and finance documents
JSON output with named field extraction
REST API for easy developer integration

You can upload your own document and check the live results.

10. Airparser - GPT-powered parsing for emails, PDFs, images.

It turns unstructured docs like emails, PDFs, HTML and even handwritten notes into clean, structured data in minutes. No templates, no code, just describe what you want to be extracted and it handles the rest using GPT-4, Vision LLMs and AI OCR.

It works in three simple steps:

1) Import the data with a wide range of options like:

you can forward emails and attachments to Airparser’s inbox
manually upload files
import documents automatically via API and platforms like Zapier and Make.

2) Instruct Airparser on the data you want to extract by creating a list of fields. You need to provide an Extraction schema and then it uses GPT with custom Large Language Models (LLMs) to ensure automatic extraction.

3) You can then export the parsed data in real time to 7000+ apps and platforms.

Here is the demo video!

Features:

Works with 60+ languages & all kinds of formats (scanned, typed, handwritten)
Visual rule builder for easy template creation
Automation by integrating with HubSpot, Slack, QuickBooks, Webhooks

11. Docling - open source AI document conversion toolkit.

Docling simplifies document processing, parsing diverse formats, including advanced PDF understanding and providing easy integrations with the gen AI ecosystem.

To use Docling, simply install docling from your package manager.

pip install docling

To convert individual documents with python, use convert(). Read more on the docs.

from docling.document_converter import DocumentConverter

source = "https://arxiv.org/pdf/2408.09869"  # document per local path or URL
converter = DocumentConverter()
result = converter.convert(source)
print(result.document.export_to_markdown())  # output: "## Docling Technical Report[...]"

They also provide proper examples in the docs, you can check them to understand most of the stuff.

Here is the video by RedHat on how Docling turns documents into usable AI data!

Features:

Parsing of multiple document formats including PDF, DOCX, XLSX, HTML, images
Advanced PDF understanding including page layout, reading order, table structure, code, formulas, image classification
Local execution capabilities for sensitive data and air-gapped environments
Plug-and-play integrations including LangChain, LlamaIndex, Crew AI & Haystack for agentic AI

Star Docling ⭐️

Comparison Table

Now that we have explored each option, let’s compare them side by side to see where each one shines. This will also make it clear why Invofox stood out at the top.

Other options that didn't make it to the list:

Some are definitely worth checking out.

That’s it. Use these AI tools to automate your document parsing workflow.

I hope you found something valuable.

Have a great day! Until next time :)