"A supply chain is only as fluid as the data that flows through it. This sentence perfectly illustrates the importance of intelligent document processing (IDP) in the logistics sector in 2025. The exponential increase in document volumes linked to the transport of goods, combined with increasing regulatory complexity, is forcing a profound transformation of processes. IDP is no longer just a technology, but a strategic lever for competitiveness and compliance for logistics operators, customs declarants and IT decision-makers.

According to Straits Research, the global IDP market was valued at 2.44 billion USD in 2024 and will reach 3.3 billion by the end of 2025, with an annual growth rate of 35.4% until 2033 1. This dynamic can be explained by increased demand in sectors such as finance and healthcare, but above all in transport and logistics, where digitalization requires document control. Companies are faced with ever larger and more varied document flows, and processing them manually generates delays, costs and errors. IDP provides an answer to these challenges by automating data extraction and streamlining the flow of information.

In this article, we review the top-performing IDP solutions of 2025, their features and differentiators. We devote a special section to transport and logistics, comparing Docloop - a specialized European solution - with its competitors (Extend, Nabu, Docsumo, Affinda, ABBYY, etc.), in an objective and factual manner.

The intelligent document processing (Intelligent Document Processing, IDP) combines advanced OCR, Artificial Intelligence and automation to extract, structure, validate and integrate data from complex documents. In 2025, IDP solutions go far beyond simple text recognition: they understand the context of information and integrate with business processes.

In concrete terms, a modern IDP platform can :

• Read all types of documents, even unstructured ones (emails, PDFs, images, handwritten forms) and automatically extract the relevant data. For example, it recognizes an invoice, contract or delivery note and can isolate key fields (header & footer information, dates, amounts, references, line-by-line details, etc.).

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• Categorize and verify information: AI enables you to categorize documents (invoice, packing list, transport order, certificate, etc.) and check the consistency of extracted data (verification of amounts, numbers, etc.), drastically reducing human error.

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• Feeding downstream systems: the IDP interfaces with the company's ERP, WMS (Warehouse Management System), TMS (Transport Management System), or EDM (Electronic Document Management) to inject data, minimizing manual re-entry and accelerating workflows.

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• Continuous learning: thanks to machine learning, these solutions improve their accuracy over time. Today's best solutions achieve over 98% accuracy, reducing processing costs by 40-80% depending on the sector and level of automation.

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In the logistics sector, IDP is particularly used to automate the processing of delivery notes, transport invoices, customs documents, CMRs, packing lists, sea and air manifests, avoid re-entry into business systems (TMS, customs, etc.) and ensure regulatory compliance (e.g. error-free customs declarations). By 2025, these solutions will be essential to absorb the growth in document exchanges, while maintaining efficiency and compliance.

The IDP market in 2025 will be served by a variety of players, from long-established publishers to innovative start-ups:

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• Multi-industry historical leaders: companies such as ABBYY, IBM or Kofax have long been offering robust OCR and automation suites that are highly valued by major accounts. ABBYY Vantage, for example, is a cloud-based platform renowned for its ability to quickly extract data from many types of document (invoices, receipts, contracts, etc.) and integrate with existing systems.

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These solutions are characterized by high precision and extensive integration functionalities, at the price of a certain complexity in implementation, and less flexibility in varying document formats. According to Gartner and Forrester, ABBYY will remain one of the leaders in the IDP sector in 2025.

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• New cloud-native platforms: new entrants such as Extend and Rossum are banking on AI and the cloud to bring greater flexibility. Extend, for example, offers a platform built entirely on LLMs (Large Language Models) and modern tools, enabling technical teams to create complex document processing pipelines in days rather than months. They often target IT teams and data scientists, providing a modern API and advanced development tools, while promising high accuracies (>95%) even on degraded scans. For its part, Rossum (of European origin) relies on a ready-to-use AI capable of automatically adapting to new formats, widely used for the capture of invoices and financial documents. Generally speaking, these "AI-first " cloud solutions offer agility and are often prized by SMEs for their rapid deployment. The use of a single model, the difficulty of handling large documents (several dozen pages), the difficulty of re-training, and the impossibility of viewing the extraction results on the original document make these solutions effective for some use cases, and less relevant for others. 

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• Specialized solutions by use or industry: some platforms focus on a specific field. For example, Nabu is an intelligent agent dedicated to customs clearance - this system manages the preparation of customs declarations autonomously from A to Z, integrating directly into existing customs software. There are also a number of offers focusing on a particular type of document: Affinda made a name for itself with its CV parser, and today offers a Document AI API capable of processing CVs, invoices, passports or bills of lading (BL) to output structured JSON. Docsumo, meanwhile, targets the needs of operational teams in finance and insurance: its ready-to-use platform automatically extracts data frominvoices, bank statements, insurance forms, etc., with pre-trained templates for these use cases and the ability to customize via machine learning. These specialists often offer powerful predefined templates in their niche, at the price of narrower functional coverage, and therefore the need to maintain several solutions to handle all user needs. 

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• No-code" and UX-oriented players: we are also seeing the emergence of solutions that prioritize a simplified user experience for business users. For example, Docloop (see dedicated section) and Docsumo are putting forward user-friendly interfaces enabling operational teams to manage part of the processing themselves, where conventional tools require the intervention of developers. Others, such as Hyperscience, offer a "human-in-the-loop" approach where the end-user can train the AI by validating/correcting extractions, which is well suited to regulated environments (banking, insurance).

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In short, the IDP 2025 offering is rich: powerful but complex generalist platforms, agile cloud solutions focused on developers, and specialized or business-oriented tools. What are the key differences? That's what we analyze below.

There are several criteria for comparing IDP solutions on the market in 2025:

• Use-case coverage: some solutions are generic multi-use cases (able to handle any type of document, from invoices to contracts to e-mails), while others are single-use case and optimized for a specific use (e.g. Nabu for customs declarations, or tools handling only supplier invoices). A solution covering all document types offers aone-stop-shop approach, whereas a hyper-specialized tool may excel at its single task, but will need to be complemented by others for adjacent needs.

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• Out-of-the-box vs. customized: the platforms differ in the degree of configuration required. The best IDPs 2025 offer templates pre-trained on common documents (invoices, passports, CVs, delivery notes, etc.), immediately usable with minimum effort. This is the case with Docloop or Docsumo, which provide ready-to-use templates for a wide range of transport, logistics, finance and other documents. Conversely, solutions such as Extend or Affinda adopt a "toolbox" approach: they offer the API and the AI engine, but it's up to the company to build and train its own templates for each specific document format (no templates are provided off-the-shelf). This offers total flexibility, at the cost of substantial technical work to achieve a high level of accuracy.

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• User experience and target audience: IT/developer-oriented solutions can be contrasted with business/operations-oriented solutions . For example, ABBYY or Extend are aimed primarily at technical teams (Data/IT) - their implementation requires specialized skills and their user interface is complex, designed for integrators or specialist administrators. ABBYY FlexiCapture is extremely powerful, but not very accessible to non-technical users, which means it is often reserved for large projects managed by IT departments or external service providers. On the other hand, Docloop and Nabu have focused on a simplified UX: Docloop offers an ergonomic web interface where a transit agent or customs declarant can supervise extractions without coding, while Nabu works in the background, integrating with existing tools so as not to upset users' habits. Similarly, Docsumo targets finance operational staff with a ready-to-use interface, although some advanced users still find it a little complex. The UX issue is a major one: a user-friendly "plug & play" solution will enable business teams to adopt it more quickly, whereas an overly technical tool is likely to remain under-utilized.

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• Support and customization: implementing IDP involves critical business processes, which is why support is so important. Vendors take different approaches to this issue. Some offer "By your side" support to help configure and train customer-specific models - as is the case with Docloop, whose technical team works with customers to fine-tune AI on their own documents, or Docsumo, which offers customization services. Others sell the tool as an " on your own" service: it's up to the company to set up the IDP according to its needs, possibly via its integrator. Extend, for example, provides exhaustive documentation and APIs, but little direct human assistance in creating your own customized pipelines. ABBYY offers training and certification, but in practice companies often need to call on an expert integrator to adapt the solution.

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• Interoperability and APIs: last but not least, the ability to integrate with other systems is a key differentiator. Most offer APIs, but not all are designed to be OEM (Original Equipment Manufacturer ) embedded by third-party editors or easily integrated into business software. Docloop has madeopen APIs a key selling point, also targeting transport/customs software publishers wishing to include IDP in their offerings. Extend and Docsumo also provide robust REST APIs, enabling you to connect their services to your workflows. In contrast, highly vertical solutions such as Nabu are more monolithic: they integrate via connectors with the customer's TMS/custom software, but are not designed to be resold or customized by a third party (no open developer program). Affinda falls somewhere in between: it does offer a Document AI API for technical integration, but the company remains the sole supplier, with no real reseller program (the offering is aimed more at end customers such as HR or accounting departments than at partner software publishers).

The comparative table below summarizes some of these differences for six representative IIP solutions:

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2025 comparison - IDP solutions (Docloop vs. competitors)

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The rise of hybrid platforms combining AI and automation

Some platforms are moving toward integrated approaches that combine traditional document extraction with workflow automation. Raft, for instance, targets tier 1 global logistics organizations with a solution that blends data extraction and business logic on top of TMS/WMS/ERPs that don’t always integrate such rules. However, despite appearances, these platforms typically require significant development effort, with workflows tailored one use case at a time. Implementation can be time-consuming and often involves rethinking and adapting existing processes. Compared to more flexible, general-purpose IDP solutions, these tools may offer less adaptability and come with higher integration overhead, with no proven better results & ROI than the IDP solutions described in this article.

By 2025, Intelligent Document Processing will be a cornerstone of digital document transformation. Over and above the immediate benefits (reduced data entry costs, faster processes, drastic reduction in data entry errors), IDP paves the way for new inter-company operating modes (data shared in real time, paperless supply chains, etc.).

For IT and business decision-makers alike, choosing the right IDP solution is not just a matter of comparing OCR rates: you need to assess the tool's business understanding, its interoperability with your ecosystem, and the ease with which it can evolve towards more complex use cases (e.g. integrating generative AI to automatically fill in missing fields, produce document summaries, etc.). Feedback shows that successful projects are those that combine high-performance technology with solid support to adapt it to the company's specific processes. Docloop is part of this new wave, positioning itself at the crossroads of AI, logistics document and transport & logistics compliance. Its multi-IA approach (intelligence adapted to each type of document, rather than a single generic model), its unified user experience, its AI Studio simplifying the work of customers' IT teams, its API enabling connection to any industry tool, and its vertical specialist DNA illustrate the direction IDP is taking: ever more intelligent, ready-to-use solutions, finely aligned with business needs. It is this match between technology and application that will ensure the success of document automation projects in the decade to come.