How to Choose the Right IDP Tool for Your Organisation

Businessman working on laptop to Document management by ai artificial intelligence process to planning information data.
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Filed under - Guest Blogs,

Pol Brouckeart at Netcall answers why does your business need the best IDP tools, common features of IDP tools to look for, what is the best intelligent document processing solution, a quick look at the IDP landscape, how to choose the right IDP tools and upcoming trends for IDP tools.

Manual document handling drains time, money and morale – and it’s getting harder to keep up as volumes rise and compliance tightens.

That’s why choosing the best intelligent document processing (IDP) software is no longer optional – it’s a necessity.

The best intelligent document processing solutions use AI to classify documents, extract accurate data (beyond OCR) and push it straight into your business systems with human-in-the-loop control where it matters.

Why Does Your Business Need the Best IDP Tools?

Manual document handling is slow, error-prone and costly. Studies show that manual data entry in processes like insurance claims can have error rates ranging from 12% to 18% (Droidal).

These errors lead to costly rework, compliance risks and customer frustration. With the right IDP solution, you can automate these processes and transform operations.

Example Use Cases Include:

  • Processing a claim that arrives as a PDF scan
  • Automatically reading and routing back-office emails
  • Supporting back-office agents with images.

Key Benefits Include:

  • Faster document processing and improved efficiency
  • Enhanced data accuracy and reduced compliance risk
  • Lower operational costs
  • Scalability to handle growing document volumes.
  • Better data management and an increase in data flow: When using an IDP tool with a process mapping software, your business can enable

What is the Best Intelligent Document Processing Solution?

There’s no one-size-fits-all answer. The best intelligent document processing solution depends on your organisation’s specific needs, industry and scale. Key criteria include accuracy, scalability, ease of use, integration, deployment flexibility and compliance.

Key IDP Capabilities That Actually Drive Impact

While many tools advertise endless features, the following five criteria are what really move the needle:

1. Accuracy and Reliability

Field‑level precision on your documents. Look for solutions with transparent confidence scoring and measurable improvement over time, so you can trust the data your teams act on.

2. Speed to Value and Usability

Low‑code/no‑code configuration is essential. Business users should be able to deploy, test and refine workflows without waiting for IT sprints.

3. Scalability and Performance

Your solution should handle high volumes, long or image-rich documents and occasional spikes without latency or cost blow‑outs.

4. Integration and Composability

Event‑driven APIs, native connectors and seamless HITL workflows to close the loop.

A Quick Look at The IDP Landscape

There’s no single “best” tool for every use case, but these well‑known options represent the spectrum from developer‑centric to business‑friendly:

  • ABBYY (FlexiCapture & Vantage) – Prebuilt skills; strong validation; volume‑based pricing.
  • UiPath Document Understanding – Deep RPA alignment; great for UiPath estates; dev‑led setup.
  • Azure AI Document Intelligence (Form Recognizer) – Strong for Microsoft stacks; pay‑as‑you‑go.
  • Google Cloud Document AI – Developer‑focused with broad model catalogue.
  • Rossum – Cloud‑native, API‑first, business‑friendly UI.
  • Instabase (AI Hub) – Powerful for complex, unstructured content and knowledge extraction.
  • Tungsten Automation (ex‑Kofax TotalAgility) – Enterprise workflows with embedded case management.
  • Hyperscience – Enterprise platform with mature HITL flows.

How to Choose the Right IDP Tools – A Pragmatic, 4‑Step Approach

With so many IDP tools promising the same outcomes, a systematic approach is the only way to cut through the noise. Making the right decision involves a structured approach:

Request a Demo

Insist on testing the solution with your documents in real-world workflows that mirror your production environment. Watch how it handles exceptions, latency and integration touchpoints. The goal is to surface deal-breakers early.

Define Your Needs

Start by identifying and listing 5–10 high‑volume/low‑quality document types slowing your teams down. Gather 25–50 real samples per type (including edge cases). This gives you a realistic dataset to benchmark potential tools against.

Consider the Total Cost of Ownership

Factor in implementation, training, data migration, support, infrastructure and ongoing updates, not just license fees. The cheapest product upfront can easily become the most expensive once it’s live.

Conduct a Vendor Assessment

Evaluate and score vendors against key criteria such as accuracy, scalability, support and compliance. Use a simple one-page scorecard to keep everyone aligned and make trade-offs visible to stakeholders.

Upcoming Trends For IDP Tools

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:

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.
  • 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.

This blog post has been re-published by kind permission of Netcall – View the Original Article

For more information about Netcall - visit the Netcall Website

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Netcall
Reviewed by: Rachael Trickey

Published On: 1st Jan 2026
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