Intelligent

Document
Digitization Platform

Azati.AI is on-demand data digitization platform for complex document workflow, powered by machine learning and computer vision.

Data Extraction and Digitization

made easy with Azati.AI

Azati.AI is on-demand data digitization platform for complex workflow, powered by machine learning and computer vision.

Many companies have accumulated large volumes of textual and graphical information in the form of paper, scanned and electronic documents in various formats.

The content of these documents is often indispensable for the company's future operations, raising the need to make this information available for machine processing.

Conventional OCR methods are not applicable for the modern business. Every particular case requires personal approach.

Azati.AI is flexible digitization platform that can be applied to any document workflow.

Our Mission

is clear and simple

We solve complex data extraction tasks, enabling our clients to automatically extract the data for which no automated extraction methods existed before. This includes documents containing unstructured data, graphs, diagrams and drawings, where the conventional OCR methods are not applicable.

Applying automation allows converting scanned data assets into machine readable format faster, cheaper and more reliably as compared to doing it manually. In addition, due to its artificial intelligence based foundation, the Azati.AI platform continuously learns and becomes more sophisticated by accumulating experience and expanding its knowledge base. Therefore it evolves on both technological and experience levels.

WE MAKE COMPLEX TEXTUAL DATA

Extraction and Digitization Process

consists of three simple steps

The Azati.AI platform provides three key capabilities that transform unstructured information into actionable data. This assumes that the initial document capture has been completed and the access to the scanned documents has been provided.

Step #1: Zone Classification

artificial intelligence classifies zones of the document

Our platform interprets the content and patterns in documents to automatically classify scanned and electronic documents into different document types, and determine the beginning and end of a document, as well as its general structure.

Recognition of the document logical structure aims at analyzing titles, headings, sections, elements, and thematically coherent parts.

With the irregular document layout structure and continuous emerging of new versions of the standardized documents coming out, the use of standard OCR engines for document classification and data extraction becomes very limited. In case of graphical documents they are not applicable at all.

On the other hand, machine learning with its self-learning abilities addresses this challenge very efficiently. The system needs only a few samples for the initial training (i.e. learning to classify the documents), and it continues to learn over time. If the system has low confidence in any document it attempts to classify, the process can call upon a human operator for confirmation. Such additional training enables continuous fine-tuning of the classification algorithms, striving for straight through processing.

Step #2: Data Extraction

the data is being automatically extracted by Azati.AI

Once the type of document is classified, our platform automatically identifies metadata within that document. Metadata is a set of data that describes and gives information about the actual content of the document. For example, if the document was recognized to be an invoice, its metadata could include the supplier account name and address, invoice number, purchase date and grand total.

The automatically extracted metadata can be used to organize, find and/or feed documents into another downstream business system, such as an accounting system, enterprise resource planning (ERP) platform, customer relationship management (CRM) system, enterprise content management (ECM) system or business process management (BPM) system.

As a step further, the automatically identified metadata can help interpret the actual content of the document, both textual and graphical data elements, and extract the document data for further processing, through the help of machine learning tools, business rules and fuzzy logic.

This step typically requires at least limited manual validation based on the calculated confidence level of the automatically extracted data, and based on the existing regulations around the given document type.

Step #3: Export Results

Azati.AI exports the collected data to your workflow systems

As a final step, our platform automatically exports the extracted data and metadata to a business process/workflow or to any downstream system. This information is immediately available for use, to gain insights into operations and customers, or enabling workers to quickly take action.

We should note, that Azati.AI has multiple output formats and Application Programming Interface, what makes it easy to integrate with any modern business software: from opensource CRMs to enterprise-grade business intelligence systems.

Even if you face any difficulties during the integration, we won't leave you alone. Our development team will help you to integrate our system into the existing infrastructure.

Frequently Asked Questions

the most commonly asked questions from our clients

Is Azati.AI an OCR Engine?

Not quite. Azati.AI includes the functionality of the traditional OCR engine and enriches it.

In its core, Azati AI uses modern ICR (Intelligent Character Recognition) techniques to power small artificial neural networks, that are the parts of the internal artificial intelligence that processes documents.

Such an approach helps the system to recognize and extract specific data from the complicated patterns: stamps, maps, waretmarks and signatures. It also processes the documents with a flexible structure.

Is Azati.AI an outsourced operation?

Hopefully, not. Azati.AI is NOT an outsourced operation.

As you might know, the majority of the document digitization systems use human powers to digitize complex documents. Usually, it is an outsourced process done by the external vendor. So there is the small probability that your confidential documents will see someone else.

Azati.AI is entirely different. We rely on cloud computing to process complex documents: all documents are processed in Amazon Cloud. Amazon Cloud is a reliable cloud computing provider known for its respect to user privacy.

Azati.AI is the big on-premise investment?

As Azati.AI is not a solid solution but it is a flexible platform, so it means that we configure it for every client. For the business, it means, that you get the personalized solution, that matches the business workflow and solves the specific goals.

We decided to use such an approach because the clients prefer to pay for the features they use, but not for the functionality that is included but never used.

Azati.AI is NOT one big on-premise investment. Azati.AI is a flexible solution that grows with your business, cutting down the costs and delivering the result you expect.

Can Azati.AI ivolved with every project?

Even as Azati.AI is the flexible platform, nevertheless it can't be involved with every project.

In some complex cases, Azati.AI requires little human help and some minor tuning and setup. Human tuning is strongly recommended when your documents contain signatures, stamps, watermarks, and maps. After minor setup, the average probability of successful document recognition is close to the 99.6%.

But there are the situations when the system is entirely unsuitable. For example, your business has a low document volume with a considerable number of different document templates. The Azati.AI can be applied as the digitization engine, but it will be less expensive to outsource the document digitization to the external vendor.

These way we provide entirely free consultations related to the document digitization and Azati.AI integration into your business workflow.

How much does Azati.AI costs and how is it billed?

There is no simple answer. It depends on many factors.

As we already mentioned, Azati.AI is the platform, but not the solid solution. In practice, that means that we customize it for every client according to the specification.

For different businesses, we provide different pricing models: from the fixed integration costs to the flexible pricing, calculated according to the amount of processed documents (units). From our experience, we should mention that final prices are usually about 31% lower, in comparison with competitors offer for the same configuration.

The best way to learn about pricing in your particular case: is to schedule the presentation and send us the sample documents. Sample documents help us to adapt your system for your specific situation.

What is under the hood?

Not the simple question. Azati.AI relies on many different technologies. There is no single technology or programming language to say it powers the platform.

To say simply, Azati.AI is an enterprise-level digitization engine powered by machine learning and sophisticated intelligent character recognition techniques.

The first versions of the engine were almost fully based on the open-source products. But now there is virtually nothing from the open-source left, during the development process we realized that there is no sense to improve open-source libraries and they are limited in some aspects.

So we developed our modules written in various programming languages to make the system work faster, more efficient and accurate. In fact, it means, that we are fully responsible for the code quality and overall platform security.

Is it possible to schedule the demo?

Yes, sure. The best way to schedule the demo is to contact us via one of the contact forms on the website.

Please, note the fact that we respect our client privacy and the data security. That means, that for the successful demo you need to provide us the sample documents.

During the demo, we will show you how the platform works, how it threatens and processes your documents and the output data extracted from your samples.

Your question is not listed?

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