Polydocs

Automate Data Capture for Infor ERP

AI

Data extraction

data extraction
von Leni

Data extraction

from a tedious activity to an efficient process

In today’s world, which is characterized by a wealth of data, the analysis and further use of data is an omnipresent topic. In this context, the extraction of data from a wide variety of documents plays an indispensable and constantly necessary role. In many companies, however, data is still often extracted and processed manually in laborious and time-consuming processes, which is associated with an increased expenditure of time and risk of error. 

So how can these dataextraction processes be facilitated and optimized to process unstructured data into a structured format suitable for easy reuse?

The biggest challenges in data extraction

The biggest challenges in data extraction lie in the large number of form variants and document versions containing unstructured data and, in some cases, irrelevant information. 

An adaptable content capture and data integration system is therefore necessary to extract the required data and process it into a structured format. And this is exactly what DOC² offers you! With DOC²’s flexible content capture, data from a wide variety of documents can be recognized, extracted and structured. This ordered data digitization allows data to be easily #processed, stored and analyzed elsewhere, resulting in greater control and increased accuracy of captured data. 

The use of an AI enables DOC² to provide simplified and structured data extraction, which increases the efficiency of these processes. It saves time, speeds up otherwise tedious turnaround times, and additionally improves the quality of the captured data.

So say goodbye to tedious and lengthy manual data typing and take advantage of DOC² in your business.

Feel free to contact us.

We’ll help you as best we can.

ContaCt
data extrction

Image credit: Header & post image from Polydocs

Time is money

time
von Leni

Time is money

Do you know what it’s like: you come into the office in the morning, full of motivation and zest for action. But then your gaze falls on the huge mountain of files on your desk and your motivation fades away. 

“How am I going to get this done?” “I definitely need more time for that.” You have certainly heard statements like these and similar ones many times or even uttered them yourself. Maybe you also say, “I can’t do more than work.” or “What I can do, I can do and that’s all I can do.” But there is always a little more, isn’t there?

You can allocate and use the time you have wisely

You bet. With the right motivation and especially the right support, you can always get a bit more out of it. You may not be able to add another hour to the day, but you can allocate and use the time you have wisely.

Let’s stay with our huge mountain of files. Your job is to process/edit all these documents. This includes typing or manually transferring documents into a system or manually comparing documents. All this takes a lot of time and the error rate in the transfer is unfortunately often just too high. This can cost the company quite a bit of money. On top of that, you are always doing the same thing day in, day out, and there is simply no time for the productive and creative tasks.

These tasks are important and need to be done, no question, but what if I told you that we can and will support you in this? In return, you get more time for other tasks, reduce the error rate and save costs as well. Too good to be true?

DOC² enables you to automate your document processes and the tedious typing and transferring of documents has finally come to an end. DOC² uses artificial intelligence and machine learning to precisely identify, classify, analyse and read your documents. It doesn’t matter if it’s a paper, file or record.

Curious?

Find out more about how DOC² can make your everyday work easier.

contact
time

Image credit: Header & Featured image from Towfiqu barbhuiya on Pexels

Digitalization – Industry 4.0 – Artificial Intelligence

Künstliche Intelligenz
von Leni

Digitalization – Industry 4.0 – Artificial Intelligence

These are all terms that we hear or read very often these days. Today we wanted to reflect on the topic of artificial intelligence (AI).

What exactly is artificial intelligence?

Where and how to use it? What benefits can it bring me and my company?

Artificial intelligence is not that easy to explain, for the simple reason that there is not even a precise definition for the term “intelligence”. Nevertheless, let’s try to explain it :-).

We can say that an AI is a mix of different technologies that enable machines to understand, act and learn with human intelligence. 

Technologies like machine learning (ML or MachineLearning), natural language processing (NLP – Natural Language Processing) as well as Deep Learning (DL) are all part of the AI landscape. 

In all areas where large amounts of data are generated, the use of an AI makes sense and is beneficial. An AI is able to objectively analyze huge amounts of unstructured data within a very short time using sophisticated algorithms, to recognize patterns in it, and to make decisions independently on the basis of these patterns. In addition, the error rate continues to fall due to the constantly growing wealth of experience. AI takes over everyday recurring routine tasks, so employees have more time to focus on tasks that require empathy and become more productive. In other words, AI should not and cannot fully replace a human, but merely support and complement them.

When combined with analytics and automation, AI can help the business achieve their goals, such as improved customer service or an optimized supply chain: faster and easier.

Automations reduce costs and bring a new level of consistency, speed and scalability to business processes.

With DOC², we want to help you automate your document processing processes. By using artificial swarm intelligence, DOC² offers you many advantages.

You want to know what they are?

Then feel free to write to us

contact
Artificial Intelligence

Image credit: Header & Featured image from Gerd Altmann on Pixabay

Comparing pears with apples

Comparing
from Leni

Comparing pears with apples

The market today is littered with offers of various products and services. For companies, that means it’s a constant struggle to stay competitive. Users, on the other hand, are spoiled for choice. It is not always easy to find the right one right away. Especially when it comes to larger investments, it is advisable to take your time and compare offers. There is no question about that. 

However, when comparing, care should be taken not to compare pears with apples.

Let’s take document processing software as an example. 

It is not possible to make a blanket statement: Software is equal to software or document processing is equal to document processing. Document processing in a document management system (“apple”) usually does not have the same capabilities/possibilities as software developed exclusively for document processing (“pear”). You may be thinking: both are for processing data after all. Yes, they are. And yet, one is a pear and the other is an apple. 

With DOC² we have a document processing solution that brings you far more benefits. DOC² uses AI swarm intelligence that allows you to continuously benefit from the experience of other customers, so you don’t have to start from scratch. It is reliable and self-learning, even with user corrections, and complex calculations are no problem.

Take your time, but not too much :-), when making your decisions and always ask yourself the questions “Am I comparing pears with apples?” or “Apples with apples?”

Feel free to challenge us with your documents 🙂

Contact
Comparing

Image credits: Header & Featured image from Polydocs

Document processing with Doc2 Version 2.0

Doc2
from

Document processing with Doc2 Version 2.0

The extraction of data from PDFs and scanned documents might not be the most interesting or challenging issue of the century. It doesn’t give you the opportunity to control a robot, play virtual games or helps you express your creativity. Instead, it’s plain diligent work, something that “KI” promised to automate but hasn’t achieved yet. Nonetheless, the processing of documents, meaning the conversion of analogue data into a digital format, describes a subtle challenge – a complex task, that is so easy and yet so difficult to resolve.

Document processing with Doc2 Version 2.0, the conversion of analogue data into a digital format – an easy and yet so difficult task to resolve.

We at Polydocs realized after completing several different projects, that document processing is omnipresent – from companies to non-governmental organizations, from little businesses to large corporations – there is always a PDF that needs to be digitalised!

The processing of documents is therefore not just difficult, it might also be in urgent need.

This blog post explains the framework for the development of document processing solutions and describes what we are working on for Doc2 Version 2.0.

Document processing with Doc2 Version 2.0 is based on the principles:

Annotations are indispensable: There is no simple nostrum. Even if you have a good model, you still must make sure to fine tune your data. Ideally you should have an annotation tool with integrated fine-tuning, or you are flexible enough to integrate the mechanism.

Generate multi-modal models: When analysing a document, we are not just relying on the text. Instead, we are taking all information (position, font size, etc.) as context, to make use of all these attributes. A plain OCR (optical character recognition) or a simple text-based approach is insufficient to resolve this task.

Always correct. OCR– and document layout models are not always perfect, hence the necessity for humans to correct the results in the system. The correction can be used to train your model or as the penultimate step before saving the results to a database.

Formularverständnis

Understanding the form

All the above-mentioned principles have been considered in Doc2. The document describes the typical document processing workflow:

Dokumentenverarbeitungsworkflow

Annotations are indispensable

Labels are indispensable for every solution in document processing. Documents tend to be very diverse, even if they have distinguishable patterns. A tool for reliable document labelling is therefore required.

Generation of multi-modal models

An additional reason why processing of documents is such an attractive problem lies in its multi-modal nature – textural and visual information is readily available. Unfortunately, rough solutions for document processing tend to only use one or the other:

Image centred approaches involve a lot of complex business rules around the frame of limitation and text placement to obtain the required information. They often rely on templates that aren’t scalable. Text centred approaches are based on NLP-pipelines for OCR-captured texts. However, text blocks are not compatible with the domain where these models were originally trained, leading to a mediocre performance.Fortunately, multi-modal models like Doc2 have the ability to learn from textural and visual information. Not only word and image itself, but also their positions are embedded for a certain document. The interactions between them are then learned, aided by predefined training goals.

The Doc² model learns from textual as well as visual information and learns about the interaction between them.

Always correct

We think that even with the most efficient document processing systems, human knowledge and experience for corrections and assessment must be incorporated. Human-in-the-loop can serve as a final inspection for the output of a model. We can reuse the corrected annotations to further refine the model and close the loop.

Final remarks for document processing with Doc2 Version 2.0

This blog post gives an outlook on our Version 2.0, describing the most important aspects of a document processing solution: an annotation mechanism, a multi-modal model and a step for assessment.

Machine learning was promised to automate manual labour. However, it looks like we hit a wall and instead started to automate creative works. In my opinion, we have optimised the search for nostrums: a big model is fed with input to receive the desired output. Manual labour, such as the processing of documents, is not like that. Instead, they are generally custom-made: you must label the data, make sure all elements of the document are incorporated and correct the output of the models – and one big model does not suffice. There are several models, extracting different things.

document processing

Image credits: Header & Featured Image from Freepik and Freepik