Bringing Value to Stakeholders Throughout the Enterprise

Enabling the enterprise to automate their most complex document-based workflows

Intelligent document processing is gaining traction because many organizations have reached the limit of what they can do with robotic process automation (RPA) and are looking to take the next step in their automation journey.

While RPA and optical character recognition (OCR) templated approaches to document automation work well with highly structured data, where the expected data is in the same place every time, they cannot handle unstructured data – such as email, Word documents, images, PDFs and more. It’s an important distinction because in most organizations, at least 80% of their data is unstructured, making it difficult for first-generation automation solutions to deal with.

A sound unstructured data automation solution, however, enables organizations to automate processes that involve unstructured data, and without huge data sets that are normally required to accurately train automation models – and that are out of reach for the vast majority of enterprises.

Instead, the IDP platform is based on a massive, pre-built database of labeled data points. It then incorporates an artificial intelligence technology known as transfer learning, which enables a model trained on one task to be used for a related task. Transfer learning obviates the need for a model to be trained on thousands of documents in order to achieve accuracy.

Indico, for example, has a base model consisting of some 500 million labeled data points. But thanks to transfer learning, it takes only about 200 documents and a few hours to train a document processing model with about 95% accuracy. That reduces the underlying data required by a factor of 100x to 1000x as compared to traditional approaches.

That dramatic reduction in data also means the Indico platform doesn’t require massive amounts of computing power, like many AI solutions do. Rather, it can run effectively on just one or two GPUs, and scale from there using low-cost CPU.

Intelligent document processing vs. RPA

It’s important to delve deep into how any given intelligent automation solution works in order to understand its true capabilities. Today, many vendors are playing fast and loose with all kinds of AI-related terms, including IDP. You may come across RPA vendors who say they incorporate AI technology to deliver what sounds like IDP. Under the covers, you will likely find the solution is merely a rules engine at heart that can’t handle unstructured data, especially at scale. In practice, “RPA + AI” solutions will likely solve only for structured and, at best, semi-structured use cases such as invoices.

A true IDP solution should be able to handle any type of data: structured, semi-structured and unstructured. Given the vast majority of data in your company is likely unstructured, only a solution that can effectively handle it will be able to accelerate your business processes and deliver transformative change. Don’t settle for less.

Automate Your Most Complex Document-Based Workflows

Automate complex business processes without data science expertise

Indico’s approach to intelligent document processing, known as Intelligent Process Automation, makes it simple and effective to build models that automate document-intensive processes normally performed by humans.

Most processes require humans to read documents, find appropriate data and enter it into a downstream system. With Indico, the business subject matter experts who understand the processes best build models to automate such processes.

Using Indico’s intuitive tools, process experts label the data points they want to extract from documents. As they do so, the model updates in real time to show predictions on how well the model will perform the task at hand. When the prediction hits an acceptable level, you’re done. Typically, it takes a few dozen to maybe 200 documents to properly train a model.

Having the people who understand the business process and the desired results actually build the models is a crucial component of the Indico approach. It turns these business people into “citizen data scientists” – even though they don’t need any data science expertise. It’s a far more rapid and accurate approach than having business people try to explain a process to a data scientist, who then goes off and builds a model. With Indico, there’s no risk of requirements being lost in translation.

All Indico tools are in plain English and are simple to use. Fully working models can be built in as little as an hour.

While Indico’s platform is simple to use, it’s built on some sophisticated cognitive AI technology that we keep behind the scenes.

One example is deep learning. Normally, users have to program a model such that the computer can understand what it needs to do. Deep learning turns that notion around and says, “Show me examples of what you want to achieve and I’ll figure out how to do it.”

Natural language processing (NLP) is likewise a crucial element. NLP enables the Indico platform to understand context in a given piece of data– whether structured or unstructured. It enables the model to “read” a document and understand it just as a human would. But it functions strictly behind the scenes; there’s no need for business users to understand what NLP is or how it works.

That goes for machine learning (ML) as well. The Indico platform is built on sophisticated ML models, but users never have to interact with them. They simply focus on delivering business benefits by building models that remove repetition and complexity from document-intensive processes, while improving accuracy.

You may find other products that incorporate deep learning, NLP and ML to address processes that involve unstructured data, but you will likely find them to be far more complex to implement. Typically they do require data science expertise, along with millions of dollars to implement and maintain.

Bringing transformational efficiencies to the enterprise

Use cases like those above make it easy to see how IDP saves companies time and money. From our experience with customers, here’s the kind of gains you can expect from Indico:

Increase efficiency, reduce costs, transform the enterprise

Perhaps figures like 85% reduction in cycle times and 4x increase in process capacity sound almost too good to be true. We can assure you they are most certainly real and add up to a rapid return-on-investment (ROI).

Consider a document-intensive process that involves 10 employees who each earn $100,000 per year, or $1 million total. Let’s say the team performs 500,000 tasks per year for a given process; that comes to $2 per task. If an IDP solution can automate 75% of those tasks – a perfectly reachable goal – the cost per task falls to just 50 cents, so the company saves $750,000 per year.

Looking at it another way, you now have $750,000-worth of employee hours to dedicate to other areas – a dramatic increase in overall capacity.

At the same time, by freeing up employees from tedious tasks, you gain soft benefits including increased employee satisfaction and productivity. Meanwhile, the IDP solution will perform the newly automated tasks with increased accuracy and consistency – because computers don’t get tired or make typos.

But don’t take our word for it. Listen to MetLife’s VP of Intelligent Automation, who recently discussed his automation journey with us. You’ll learn how MetLife went from automating simple tasks with RPA to using IDP for unstructured document processing automation. Over the next 5 years, MetLife expects to realize $100M in value through hours saved by automating processes involving unstructured data. You can watch the full interview here.