Top 10 Best Intelligent Document Processing (IDP) Solutions

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If you built or integrated an automation solution into your systems, you already know the bottleneck is rarely a missing API. It is the unstructured mess flowing through mailboxes, shared drives and portals: invoices and order confirmations, RFQs and shipping docs, contracts and checklists, quality and compliance evidence that causes the real struggle. Intelligent document processing (IDP) is what turns that stream into structured data with enough context to drive real workflows.

We compared 10 IDP options across the criteria that matter in production: features, document coverage, integration effort, best‑fit use cases and how pricing typically works. 

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The 10 best intelligent document processing software

1) turian (AI agents with built‑in IDP)

Features

turian’s AI workers combine document understanding with reasoning and communication: they read emails and attachments, interpret context, ask clarifying questions when needed, update ERP or CRM, and route exceptions to humans. We use LLMs for extraction and validation, plus human‑in‑the‑loop review and a BI layer for process analytics.

Types of documents

turian’s AI agents read and understand any type of documents, whether structured or not, including sales orders, purchase orders, contracts, RFQs, and bills of quantity, and in any format: plain text emails, PDFs, scanned documents, and images. No template or layout needed.

Pros: 

• End‑to‑end workflow focus rather than point extraction. From document detection on your inbox or upload, to entry of key data points in your ERP, CRM, or other systems, turian AI agents automate your processes entirely
• Automated email and inbox handling, including detecting documents and attachments and drafting replies 
• Vast integration capabilities 
• Human-in-the-loop logic that enables you to set the workflow to deviate certain cases to human team members
• EU compliant
• ISO certified 

Cons:

• Best value when adopted as a workflow layer, not only as an API for OCR‑style extraction.

Integration easiness: 

• No model training needed
• Low‑code configuration features
• The technical team sets the integration and ensures maintenance follow-up
• Integrates with +20 ERP systems, most popular CRM systems, including Hubspot and Salesforce, all major email and messaging platforms, and +8 databases and data warehouses.

Best for: 

• Mid‑sized companies looking for AI workers that run procurement and inside sales flow end-to-end. 
• Companies in the manufacturing, wholesale, logistics, and supply chain industries.

Pricing: Custom based on volume and scope. There is no standardized plan, but rather a schema that adapts to the client's needs.

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2) ABBYY 

Features:

• Cloud-first IDP platform with prebuilt “skills” for 150+ document use-cases.
  
• Strong classification/splitting capability.
  
• Data-validation rules included.
  
• Focus on straight-through processing and human validation when confidence is low.

Types of documents:

• Structured, semi-structured and unstructured.
  
• Pre-built skills for invoices, purchase orders, receipts and more—including international invoice packs. 

 Pros:

• Mature library of pre-trained skills.
  
• Strong classification and splitting capabilities.
  
• Enterprise-grade controls.

‍Cons:

• Skill licensing and tuning can feel heavy for narrow use-cases.
  
• Pricing is typically quote-based and tied to page volumes—public price sheets vary regionally.
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‍Integration easiness:

• REST APIs, marketplace assets.
  
• Often paired with AP systems and ERPs.

‍Best for:

• Enterprises standardising capture across many business units with a catalogue of prebuilt models.

‍Pricing:

• Page-based subscriptions and bundles; treat public info as directional only.
  
  

3) UiPath 

Features:

• Pre-trained models for common documents and active-learning for custom models.
  
• Validation Station for human-in-the-loop review; tight integration with RPA.
  
• New “IXP” (Intelligent Xtraction & Processing) capability targets unstructured and complex documents.

‍Types of documents:

• Invoices, receipts, purchase orders, IDs/passports and more via out-of-the-box packages + custom extractors.

‍Pros:

• End-to-end with robots (RPA + IDP).
  
• Good validation-UX.
  
• Broad community knowledge base.

‍Cons:

• Licensing can be complex (page-licenses + AI/Platform units) and budgeting can challenge.
  
• Tuning multiple extractors demands discipline and expertise.
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‍Integration easiness:

• Native to UiPath Studio; headless API usage possible; lots of connectors in the UiPath ecosystem.
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‍Best for:

• Teams already orchestrating with UiPath RPA who want first-party IDP.
  

‍Pricing:

• Page-based Document Understanding licenses + per-page AI/Platform Units for modern projects. Official docs describe the metering model but list prices are not fully public. 
  
  

4) Rossum

Features:

• Cloud-native IDP platform built on AI and computer-vision for document understanding.
  
• Supports multi-channel document intake, master-data matching, duplicate detection, custom functions, webhooks and reporting on document flows.
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‍Types of documents:

• Transactional paperwork: invoices, purchase orders, bills of lading and other back-office documents.
  
• Multi-channel ingest: email, EDI, uploads.
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‍Pros:

• High G2 user rating (4.5/5) reflecting strong user satisfaction.
  
• Recognised as “Strong Performer” in the 2025 Gartner Voice of the Customer for IDP Solutions report.
  
• Focus-tight on AP/order workflows with modern API capabilities.

‍Cons:

• Mostly suited for transactional back-office scenarios, less focus on highly unstructured documents.
  
• Advanced customisation may require vendor services (so cost/time may climb).

‍Integration easiness:

• Prebuilt integrations with major ERPs (SAP, Coupa, NetSuite, Workday, Microsoft Dynamics) plus webhook/event layer for ERP posting & approval flows.

Best for:

• Finance and operations teams consolidating AP/AR intake, especially where email or multi-ingest channels dominate.

‍Pricing:

• Quote-based; typically tied to document or page volumes and workflow complexity.
  
  

5) Microsoft Azure AI Document Intelligence

(formerly Form Recognizer)

Features:

• Cloud-based AI service for document understanding: OCR, text/key-value extraction, table parsing.
  
• Supports custom models, container/edge deployment.
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‍Types of documents:

• Broad coverage: invoices, receipts, IDs, contracts, scanned documents.
• Suitable for structured and semi-structured content; layout-agnostic capability.
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‍Pros:

• Enterprise-grade Azure stack, robust SDKs, strong integration with Azure ecosystem.
  
• Transparent pricing page.

‍Cons:

• You need to assemble workflows yourself (less out-of-the-box end-to-end IDP).
  
• For advanced schemas and human-in-the-loop review one may need additional services.

‍Integration easiness:

• Excellent developer tooling: SDKs, Azure Functions, Logic Apps, AKS/ACI, containers.
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‍Best for:

• Developers and teams building IDP into a broader Azure architecture or needing data residency or container/edge deployment.
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‍Pricing:

• Transparent per-page and per-feature pricing tiers (see Azure pricing site). 
  

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6) Google Cloud Document AI

Features:

• Processor library for enterprise OCR + classification/extraction + custom training + human review tool.
  
• Integration with Google Cloud storage, BigQuery, pipelines.
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Types of documents:

• Extensive processors: invoice, purchase order, expense, general OCR supporting 200+ languages.
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Pros:

• Strong pre-built catalogue and language support.
  
• Clear per-page pricing examples.
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‍Cons:

• Human review UI is good but not a full case-management stack.
  
• Pricing and plans vary by region/processor; can be confusing.
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‍Integration easiness:

• REST API, client libraries, integrates well with GCP data engineering tools.
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‍Best for:

• Engineering teams standardising on Google Cloud and who need a processor catalogue + clear unit pricing.
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‍Pricing:

• Per-page, per-processor; tiered examples available on pricing page. 
  
  

7) Amazon Textract

Features:

• OCR plus layout understanding, specialized APIs for invoices, receipts, IDs, tables; “Queries” feature for targeted field extraction.
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‍Types of documents:

• General documents, forms, tables, invoices/receipts, IDs, lending documents; includes handwriting support (to a degree).
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‍Pros:

• Simple pay-as-you-go model, mature AWS SDKs, massive scale.
  
• Strong cross-integration with AWS services (S3, Step Functions, Lambda).
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‍Cons:

• Out-of-the-box extraction may need post-processing or extra logic to reach AP-level accuracy.
  
• Some users report language support or table/complex-layout handling limitations.
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‍Integration easiness:

• Excellent within AWS ecosystems.
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‍Best for:

• Developers wanting low-friction, usage-based API inside AWS stack and comfortable building workflow around it.
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‍Pricing:

• Per-page rates by feature and volume; free tier available for initial testing. 
  
  

8) Tungsten Automation TotalAgility / Transact

(formerly Kofax)

Features:

• Mature capture & orchestration platform: multichannel capture, classification, extraction, workflow orchestration.
  
• Incorporates Generative-AI powered “Copilots” for extraction and insights per recent releases.
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‍Types of documents:

• Broad enterprise usage: AP, mortgage, claims, government, records.
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‍Pros:

• Deep enterprise footprint, strong connector library, both on-prem and cloud options.
  
• Recognised as Leader by Everest Group for IDP.
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‍Cons:

• Heavier platform to implement; may feel large/complex for leaner teams.
  
• Licensing/price publicly less transparent.
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‍Integration easiness:

• Marketplace connectors for SAP etc; extensive documentation.
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‍Best for:

• Enterprises consolidating legacy capture systems with modern IDP and needing full orchestration control.

‍Pricing:

• Quote-based, solution-specific.
  
  

9) Hyperscience

Features:

• IDP platform geared to messy, real-world inputs: handwriting, low quality scans, unstructured/long-form documents.
  
• Includes human-in-the-loop, analytics, model lifecycle features.
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‍Types of documents:

• Structured forms through unstructured records: claims, public sector, logistics paperwork.
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‍Pros:

• Strong on handwritten and low-quality image processing (accuracy up to 93-95 % reported).
  
• Good enterprise controls, audit trails.
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‍Cons:

• Typically sold as full platform, custom contracts; fewer pre-built “invoice only” shortcuts compared to invoice-centric vendors.
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‍Integration easiness:

• APIs and enterprise deployment options.
  

‍Best for:

• Organisations with heavy handwriting, public-sector forms, complex long-form content requiring precise supervision.
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‍Pricing:

• Contract-based; custom terms and arrangements.
  
  

10) Indico Data

Features:

• Platform aimed at intake of unstructured data: transfer-learning technology, hybrid AI architecture (discriminative + generative).
  
• Template-free processing; fewer labeled examples required.

‍Types of documents:

• Insurance submissions, loss runs, claims correspondence, healthcare and financial statements; unstructured text/tables.
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‍Pros:

• Good fit for complex unstructured sets and specialty intake (insurance, finance).
  
• Industry focus (insurance underwriting, claims).
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‍Cons:

• Less out-of-the-box catalogue compared to invoice-centric platforms; pricing is quote-based.
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‍Integration easiness:

• APIs and professional services; used in bespoke model-centric settings.
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‍Best for:

• Carriers and banks that need bespoke models for complex document packets rather than standard template-based extraction.
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‍Pricing:

• Quote-based; custom engagement rather than fixed plans.
  
  

What to consider when choosing an IDP solution

Start from the workflow, not the PDF: Extraction accuracy matters, but the real transformation and ROI lives in what happens next: posting extracted data to your ERP or CRM, emailing a supplier. Considering a supplier that goes beyond data extraction is what sets the difference between a tool and an end-to-end automation system. Simply extracting data from a PDF won’t change your business overnight, but full workflow automation will save time, reduce errors, and let your team focus on strategic aspects of the business.

Document diversity vs. Specialization: You need to decide what matters the most to your processes: a wide variety of document types coverage, or hyperspecialization in one type in particular? A model that is excellent at invoices may underperform on order confirmations, for example. It’s important to evaluate depending on your business needs: do you process invoices almost exclusively, or do you handle dozens of sales orders, bill of quantities, and contracts on a daily basis?

Human‑in‑the‑loop is a feature, not a failure: Review stations and selective routing close long‑tail gaps while providing labelled feedback. Getting flagged documents is not a negative thing, it’s actually 

Integration debt is real: Email ingestion, ERP systems, are the hidden 80 percent. Ensuring that the IDP solution you choose integrates with the systems your team uses on a daily basis is essential. Without proper communication between systems, automation stalls and your processes won’t see the differences and benefits provided by real automation. 

Security and data privacy

Choose vendors that support encryption both in transit and at rest, audit logs, fine-grained access controls. Always take a look at compliance considerations: is the platform compliant with relevant regulations for your area of operation? This is particularly important in the EU, where regulations about data privacy and user security are very important and your company may be in legal trouble or incur in fines if you do not pay special attention to this factor.

Check also for certificates or standards (SOC 2, ISO 27001, etc.) and ask how the vendor handles data residency if you operate globally. For sensitive domains (finance, insurance, public-sector) you’ll want traceability: who changed which extracted value, on what evidence, when? Audit trails matter.

Pricing models and total cost

• There are three broad patterns:
  
  
  • Per-page consumption (e.g., some cloud services).
    
    
  • Platform licensing + usage metering (e.g., combination of base fee + pages/units).
    
    
  • Quote-based platform subscriptions tied to document/page tiers or entitlements.
    
    
• When comparing quotes check what is included: model training/maintenance, storage, review seats, API calls, integrations.
  
  
• Consider your hidden costs: tuning/extractor construction, change-management, human review, exception handling.
  
  

European specifics: ensure the solution you choose considers EU-specific regulations and compliance matters. Make sure your IDP solution can handle structured-data formats (XML, UBL) and map to/validate European standards around E-rechnungs rather than only PDF invoices. For compliance documents (e.g., Corporate Sustainability Reporting Directive (CSRD), CBAM, REACH) you need governance: audit logs, review trails, metadata export, role-based access.

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Wrap Up

IDP has matured beyond OCR engines and point extractors. The new baseline is a system that can read varied documents, reason over context, interact with people by email or UI when needed, and commit clean data to your systems with an audit trail. The right choice depends on the team you have and the workflow you want to own.

Whichever route you take, treat IDP as a product. Wire in review and feedback loops, monitor extraction quality like a KPI, and keep your business rules close to the data. The organisations that do this are the ones shipping reliable automation, not demos.

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