When you have complex documents with tables, pics, lots of variation, more data elements, free-flowing docs.

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IDP can understand the data, context, create insights, and generate a narrative.

The wrong approach can ki l l your ROI.Extracting data from documents?

You need to extract data from documents so you can feed a content-driven process. You’ve got three choices to extract the data: manual, old school OCR and an innovative new approach called Intelligent Data Process (IDP).

Which one is right for you?

First, let’s throw out manual because… it’s manual. It’s slow, expensive, and it doesn’t scale. And there is now an alternative (hint IDP) that works better than humans on complex documents.

That leaves OCR and IDP. Let’s answer your top questions so you can decide which is best for your needs.

When should I use IDP or OCR?

Other than data extraction, what can it do?

IDP is built on an AI-native platform where machine learning is the core technology.

IDP uses machine learning techniques to automatically learn and improve over time.

No, It is template free.

Greater business benefits and ROI can be achieved because IDP extracts more information and insights.

The lowest our customers start is 5,000 docs per month.

What is the core technology of each?

Does it improve accuracy over time?

Does it use templates to process documents?

What business case can I expect?

What is the minimum processing volume?

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Data extraction is about it.

When you have simple, structured docs that fit into a template.

The OCR engine is the defining technology although it may include some AI as an afterthought.

It’s a manual process that might be guided by a tool.

Yes, OCR uses templates which are expensive to build, maintain and manage.

OCR business case is based on labor reduction for simple docs.

No lower limit for OCR. It's fine with a 100 pages a month.

OCR IDPVS