What is Intelligent Document Processing (IDP)?

18th December 2025

by Pol Brouckaert

Did you know that 80% of business processes still rely on manual document handling, costing organisations millions in errors, delays and inefficiencies? From invoices and claims to emails and contracts, document-heavy workflows slow everything down.

Intelligent document processing (IDP) changes that. By using AI to read, understand and extract data from documents — whether PDFs, scans, images or emails — IDP transforms unstructured content into clean, actionable information. This means faster processing, fewer errors and a scalable way to accelerate digital transformation.

In this article, we will answer the following questions:

1. What is intelligent document processing?
2. How does intelligent document processing work?
3. Intelligent document processing examples
4. Core technologies behind intelligent document processing
5. Key benefits of intelligent document processing
6. Challenges and considerations when using IDP
7. How IDP fits into the intelligent automation ecosystem
8. Emerging trends in IDP for 2025
9. Liberty IDP, your intelligent document processing solution

What is intelligent document processing?

Intelligent document processing (IDP) is an advanced workflow automation technology that uses AI to scan, extract, classify and organise meaningful information from large volumes of documents.

Instead of manual reading and data entry, IDP ingests files from multiple channels, identifies key data fields, validates accuracy and routes information into downstream systems. It works across structured, semi-structured and unstructured content — including invoices, claim forms, emails and images — delivering faster, more scalable and highly accurate processes.

IDP can operate fully automated or with human-in-the-loop checks for complex scenarios, making it essential for modern document-driven workflows.

How does intelligent document processing work?

So, how does intelligent document processing work in practice? Most IDP platforms follow a similar sequence of processing events, which we refer to as the IDP pipeline.

Documents with structured or unstructured data are ingested, interpreted, extracted, classified and structured. Data quality is checked with confidence scores and, where needed, by humans. Then the cleaned data is integrated into business systems without manual re-keying, for example into ERP or CRM platforms.

You can think of it as a flow like this:

Document intake

IDP ingests documents from email, scanners, customer portals, cloud drives and business applications, consolidating them into a single, controlled process.

Pre-processing

Files are then run through a number of pre-processing steps that guarantee consistent visual data quality and optimal readability, as well as uniform data formats regardless of the input data file formats.

Classification

The system recognises the document type, for example an invoice, application, contract, medical attestation, parking permit or complaint, and applies the right extraction and routing logic.

Data extraction

The platform then interprets the content, especially unstructured text such as emails, letters, claim descriptions or medical notes. AI models identify what each piece of information means and map it to fields such as IDs, dates, amounts, line items or specific clauses.

Validation

Accuracy is checked using confidence thresholds and business rules. High confidence data can flow straight through, while lower confidence fields or anomalies are routed to human reviewers through a human-in-the-loop interface.

Distribution

Validated, structured data is delivered into downstream systems such as ERP, CRM, policy administration, case management or data warehouses, ready for automation, analytics and reporting.

Intelligent document processing examples

IDP becomes tangible when you see it in real organisations.

At Input For You, a document processing provider for insurers, Liberty IDP sits at the heart of claims handling. Instead of large teams rekeying data, the platform classifies incoming documents, extracts key fields and validates them with human-in-the-loop checks where needed, delivering 99.5% accuracy, around 80% reduction in claim processing time and straight- through processing above 70% for key document types.

European insurer, Baloise, uses Liberty IDP to read and route all incoming claims emails. IDP interprets each message and its attachments, decides which process or team should handle it and prepares the data for straight-through processing, turning what many see as an email routing problem into an IDP use case. Baloise has quadrupled STP from 15% to 65% while processing roughly 11,000 documents per day and creating more workforce flexibility.

South Hams District Council applies Liberty IDP to automate parking permit schemes. Residents submit photos of V5C forms, lease agreements or Motability contracts taken on a mobile phone; Liberty IDP classifies the documents, extracts the data and feeds it into the council workflow. This enables faster turnaround for residents and a significant reduction in manual effort for the council team.

Core technologies behind intelligent document processing

Under the hood, IDP combines several AI and automation technologies. Together, they turn static documents into machine usable data and decisions that conventional data capture cannot deliver.

1. Optical Character Recognition (OCR)
   OCR converts images of text, such as scanned PDFs or smartphone photos, into machine readable characters. It is the foundation for many document workflows, but on its own, OCR just turns pixels into text and does not understand what that text means.

1. Natural Language Processing (NLP)
   NLP helps the system interpret language, context and semantics. This is vital for unstructured documents like letters, emails, contracts or medical reports, where the same field can be written in many different ways.
2. AI and Machine Learning (ML) or Deep Learning
   These models learn from historical documents and user feedback. Over time, they improve classification accuracy, adapt to new layouts and handle edge cases more robustly.

1. Computer vision
   Computer vision models interpret the visual structure of documents. They recognise logos, checkboxes, signatures, stamps, tables and layout regions, allowing IDP to process complex or low-quality images and multi-page documents, not just clean PDFs.
2. Domain specific AI models
   Many organisations use models tuned for particular document types or industries. For example, a model trained on insurance claims and medical attestations will typically outperform a generic one for that domain, especially when combined with human-in-the-loop feedback and continuous learning.
3. Document generation
   Because the content is now structured, some IDP solutions can also generate derived documents, for example, anonymised or redacted versions, summaries or letters that safely reuse information without exposing sensitive details.
   

Together, these technologies position IDP as the brain of document processing, far beyond what traditional OCR or rigid template-based capture can achieve.

Key benefits of intelligent document processing

From a business strategy perspective, the benefits of intelligent document processing go beyond simple time savings. They reshape how document-centric processes are designed, governed and scaled. When you look at the benefits of intelligent document processing, several themes come up repeatedly.

Increased accuracy: AI + human validation reduces errors

Combining AI extraction with confidence scoring and human-in-the-loop validation reduces errors from manual rekeying and supports human-level or better accuracy, even on long or complex documents.

Cost savings & efficiency: Automates repetitive tasks

Automating repetitive reading, sorting and data entry tasks cuts processing costs and frees staff to move from low-value typing to higher-value exception handling and customer work.

Enhanced scalability: Handles peaks without extra staff

Once document flows are automated, scaling is a matter of configuration and compute, not hiring and training larger teams, so peaks and new products can be absorbed more easily.

Faster processing: Cuts cycle times from days to minutes

End-to-end IDP-based workflows reduce cycle times from days or weeks to hours or minutes, improving decisions, customer experience and SLA performance.

Improved compliance: Standardised rules to support GDPR

Standardised rules for how documents are processed, stored, redacted and audited help support GDPR and sector-specific regulatory requirements.

Challenges and considerations when using IDP

Like any strategic technology, IDP is not a magic wand. There are common challenges that business and IT leaders should anticipate if they want programmes to succeed beyond a proof of concept.

1. Data quality and document variability
   Poor scans, low-resolution photos and heavily handwritten content impact extraction accuracy, so capture channels and models need to be tuned on realistic data.
2. Integration with legacy systems
   IDP only delivers value when its output is connected to core systems. Low-code integration and RPA can help bridge gaps where APIs are limited.
3. Lack of clear objectives and KPIs
   Programmes need clarity on target processes, volumes, automation rates, quality thresholds and business outcomes. These should be revisited as the system learns.
4. Governance, security and explainability
   Sensitive customer, patient or financial data requires clear rules for where models run, how data is stored, how reviewers work and how decisions are audited. Netcall’s IDP offering is designed to give this level of insight and control and is backed by ISO 27001- certified security.
5. Change management and user adoption
   Operations, IT, compliance and business owners all need to be involved so people see IDP as an enabler, not a threat and trust the results.
   

The choice of IDP tool is critical. Platforms vary in accuracy, long document handling, ease of use and the depth of human in the loop support.

For a deeper dive into selection criteria and the vendor landscape:

How IDP fits into the intelligent automation ecosystem

IDP is often the front door to intelligent automation. It turns unstructured content into structured, machine-readable data that other tools can act on.

A common pattern is to pair IDP with robotic process automation (RPA). IDP reads and validates the content of incoming documents, while RPA bots use that data to update records, move cases between systems, trigger notifications, or kick off downstream workflows.

For an introduction to this technology: What is RPA?

IDP also integrates naturally with low-code application development and case management. Extracted data populates forms, drives decisions and powers dashboards. The combination of IDP with low-code is often the most practical way to design human-in-the-loop processes such as review screens, exception queues and supervisor approvals without long development cycles. In the Liberty platform, for example, Liberty IDP works alongside Liberty Create, Liberty RPA and Liberty Converse, allowing organisations to design complete digital journeys that start with a document and end with a resolved outcome.

Emerging trends in IDP for 2025

The IDP market is evolving rapidly. New tech, changing data volumes and tighter regulations are reshaping what “good” looks like. Here are the trends worth paying attention to and what they actually mean in practice:

Generative AI expansion: Tools are moving beyond data extraction into summarisation, semantic search and Q&A, now paired with stronger validation layers and guardrails to keep outputs reliable.

Hybrid AI approaches: Expect tighter integration of large language models (LLMs) with classical machine learning, giving systems the flexibility to handle both unstructured and structured content without sacrificing accuracy.

Verticalised solutions: Vendors are packaging domain-specific offerings for sectors like banking, insurance and the public sector, drastically reducing setup and training time.

Composable automation: IDP is becoming the “front door” to broader workflows, feeding data directly into case management, ERP, CRM and customer systems.

Cloud-native and low-code adoption: Cloud-based architectures and low-code platforms are accelerating deployment, reducing complexity and making IDP more accessible for enterprises.

ModelOps maturity: Governance, monitoring and continuous learning are now being baked into everyday operations, reducing drift and compliance risk.

Lower implementation costs: As vendors standardise integration patterns and pre-train models, the reliance on costly professional services is dropping. For a deeper dive, see our article Intelligent Document Processing 2.0: How AI Elevates IDP from Useful to Unstoppable.

“IDP is evolving fast. In 2025, it’s not just about data extraction – it’s about intelligent workflows powered by Generative AI, hybrid models and document intelligence. Cloud-native architectures and low-code capabilities are making IDP more accessible and easier to integrate, while verticalised solutions and ModelOps maturity ensure scalability and compliance. This shift positions IDP as a strategic enabler for digital transformation, not just a back-office tool.”

Pol Brouckaert

Director Netcall EU

Liberty IDP – your intelligent document processing solution

Netcall’s Liberty IDP is an AI- powered intelligent document processing solution that transforms unstructured and semi-structured documents into clean, actionable data. It combines multi-modal AI, human-in-the-loop control and intuitive, prompt-driven configuration, so teams can automate high-value document flows quickly, without losing oversight. Whether you need to handle small, focused use cases or large-scale operations processing tens of thousands of documents per day, Liberty IDP scales effortlessly.

Integration is simple:

1. Direct APIs for modern systems
2. RPA connectors for legacy platforms
3. Low-code tools to build review screens, exception queues and dashboards, fast.

As part of Netcall’s broader intelligent document processing software offering, Liberty IDP is natively integrated with Liberty RPA and Liberty Converse for CX, so document understanding can power complete, end-to-end digital journeys.

Ready to cut your document processing time?

About the author

Pol Brouckaert

Director of Netcall EU

Pol leads the company’s expansion across continental Europe from the Brussels office. He joined Netcall through its 2024 acquisition of Parble, an intelligent document processing (IDP) company where he served as CEO. Pol has built a career at the intersection of strategy, technology and financial services. Earlier, he worked as a strategy consultant at BCG, advising leading banks and insurers on digital and business transformation initiatives internationally. His expertise spans strategy, AI and technological innovation. Together with his team, he has helped numerous companies harness the benefits of intelligent document processing, one of the most mature and pragmatic use cases of AI.