Document-heavy workflows are steadily increasing across banking and finance, insurance, logistics and other regulated industries. Claims, invoices, bank statements, financial reports and forms all arrive in different formats, layouts and levels of quality. And they keep coming.
For many teams, the challenge isn’t digitizing documents anymore. It’s reliably capturing unstructured data at scale and turning it into decision-ready outputs without slowing the business down.
That’s why the definition of the ‘best’ intelligent document processing (IDP) software has shifted. It’s no longer about converting PDFs into text. It’s about understanding documents as humans do, handling variation and ambiguity and integrating clean data directly into downstream workflows.
In 2026, this shift is being driven by large language models (LLMs) and agentic IDP architectures that go far beyond traditional OCR or machine learning-based extraction. For teams already thinking about automation strategy, this shift toward agentic IDP is reshaping how document-heavy processes are designed, scaled and governed across the enterprise.
This guide is designed for teams evaluating IDP vendors today, helping you understand what matters, how leading platforms compare and why architecture now determines long-term success.
What is an intelligent document processing solution?
Intelligent document processing has evolved rapidly over the last decade.
- OCR focused on text recognition.
- Machine learning-based extraction added pattern recognition and templates.
- IDP combined OCR, ML, rules and workflows.
- Agentic IDP now orchestrates multiple AI techniques, OCR, validation and human review, to produce verifiable outputs.
Many organizations still group OCR, RPA and IDP together, even though they solve very different problems in modern automation stacks.
A true IDP solution does much more than digitize documents. It enables organizations to capture unstructured data from messy, real-world inputs such as scanned PDFs, handwriting, forms and multi-document bundles.
Key capabilities of a modern IDP platform include:
- Ingesting any document type, format or layout
- Automatically splitting and classifying documents
- Extracting structured and unstructured data
- Validating, cross-checking, grounding and transforming outputs
- Orchestrating workflows and integrating with business systems
- Supporting human-in-the-loop review when needed
- Offering mechanisms for traceability and governance
When assessing the best intelligent document processing software, teams should focus on accuracy, flexibility, adaptability, configuration speed, integration ease, security and scalability. Once models are running, most platforms process documents quickly. The real difference lies in how fast you can configure them, how well they adapt to changing business processes – from new document variations to evolving fields and validation rules – and how quickly you can drive a return on investment.
Key features of the best IDP software
The strongest IDP platforms deliver clear benefits for both business and technology leaders.
1. High accuracy on unstructured data
Accuracy underpins trust. For business leaders, higher accuracy means fewer errors, less rework, faster turnaround times and lower operational risk. For technologists, it means predictable outputs that can be safely automated. For both leaders, it means data you can count on.
2. Ability to handle complex, mixed documents
Real workflows rarely involve a single document type. Leading IDP solutions handle multi-page, mixed-content files such as bank statements, payslips, identity documents, invoices, medical reports and contracts within the same pipeline.
3. Fast configuration without training cycles
Traditional machine-learning-based systems require retraining when layouts or fields change. Modern agentic IDP systems learn instantly from corrections, dramatically reducing setup time and ongoing maintenance.
4. Validation, grounding and verification
Validation and grounding ensure extracted data can be traced back to source evidence. This prevents hallucinations and supports high-stakes use cases where trust and auditability matter.
5. Human-in-the-loop user interface
A strong review interface gives teams confidence in automation and allows humans to intervene only when necessary. Alerts and exception handling keep workflows moving without constant oversight.
6. Workflow automation and system integration
Best-in-class platforms integrate seamlessly with ERP, CRM, RPA, lending and claims systems. API-first design and orchestration capabilities are essential for end-to-end automation.
7. Scalability across volumes and document types
IDP should enable growth without linear increases in headcount, supporting higher volumes, more document types and new workflows over time.
Best intelligent document processing solutions in 2026
How do the leading IDP vendors compare to Affinda? Let’s explore.
Affinda
Strengths
- Agentic document processing with validation and grounding
- Model memory that learns instantly from corrections
- Fast time-to-value with quick setup
- High accuracy on unstructured and semi-structured documents
- Flexible integrations using APIs and the Integrations Agent
- Handles multi-document PDFs with automated splitting and classification
Best for: Enterprises needing high accuracy, rapid onboarding and flexible automation across complex document workflows.
ABBYY Vantage
Strengths
- Established incumbent with strong OCR heritage
- Broad enterprise adoption
Limitations
- Template and ML-driven approaches require retraining
- Retraining cycles often required for new layouts or fields
Tungsten (formerly Kofax)
Strengths
- Broad automation suite
- Mature workflow tooling
Limitations
- Complex implementations
- Less flexible when schemas or document structures change frequently
Rossum
Strengths
- Strong focus on accounts payable automation
- Clean, modern interface
- Uses newer AI approaches beyond traditional ML
Limitations
- High minimum pricing compared to usage-based models
- Optimised for AP, not broader, multi-team document workflows
- Limited as a centralised platform for organisation-wide automation
Hyperscience
Strengths
- AI-first positioning
- Developer-friendly approach
Limitations
- Requires significant configuration work
- Not well suited to adapt to new formats and variations of documents
Nanonets
Strengths
- Easy to use, no-code orientation
- Well suited to SMB and mid-market teams
Limitations
- Pricing can be difficult to predict due to block-based and component-based usage models
- Not designed for enterprise complexity
- Accuracy variability with unstructured documents
Where Affinda comes out on top
Our agentic architecture enables verifiable outputs, instant learning and lower operational overhead. While many platforms plateau due to ML limitations, our platform continues to adapt in production, learning instantly from every document and correction. Built-in validation, audit-ready workflows and human-in-the-loop controls make it well suited to regulated, document-heavy environments, while configurable integrations and fast onboarding accelerate time to value.
How to capture unstructured data from documents
A practical IDP framework typically follows six steps:
- Ingest any file format: PDFs, scans, images, camera photos and multi-document bundles.
- Split and classify documents: Automatic detection reduces manual sorting and accelerates downstream processing.
- Extract structured and unstructured fields: Platforms like Affinda’s infer meaning from context using LLMs combined with reading order algorithms, retrieval augmented generation and OCR. This enables extraction of complex fields such as tables, groups, signatures, handwriting, images and checkboxes.
- Validate, verify and transform: Cross-check totals, dates and entities. Match outputs to your system of record and apply transformations such as name or date formatting.
- Human review where needed: Alert users only when exceptions occur, maintaining confidence without slowing workflows.
- Integrate with business systems: Push clean data into ERP, CRM, RPA, lending and claims platforms.
How to choose the best IDP solution: a checklist
For business leaders
- Accuracy benchmarks that allow for straight-through processing
- Time-to-value and ease of rollout
- ROI through faster turnaround, reduced risk and higher-value work for teams
- Vendor credibility and long-term roadmap
For technology leaders
- API-first design and integration ease
- Configurable schemas without retraining
- Enterprise-grade security and compliance controls
- Support for multiple document types, layouts and formats
Why Affinda leads the next generation of IDP
Affinda’s platform is built for modern document automation:
- Agentic, LLM-powered extraction
- Model memory enabling continuous, instant learning
- Evidence-based, grounded outputs
- Enterprise-grade security
- Customizable integrations
- Access to experienced engineers when needed
- Fast onboarding with clear ROI
Choosing an IDP platform that will still work tomorrow
The best intelligent document processing software delivers more than OCR. It captures unstructured data accurately, adapts as documents and business requirements change, and integrates cleanly into workflows – acting as a long-term partner rather than a point solution.
As organizations move beyond experimentation, agentic IDP has become essential for reliable, scalable automation. For enterprises seeking fast time-to-value, decision-ready data and futureproof architecture, Affinda stands out as a leading choice.
Ready to see it in action? Explore Affinda Platform or try it free on your own documents.