Infrrd AI Enabled Intelligent Document Processing for Complex Documents

“Intelligent data capture can achieve up to 95% accuracy and processes 12x faster than manual processing.” While traditional  OCR solution  may still be a better option for a few organizations, it fails to address critical challenges of graph extraction like identifying trends. Moreover, it also fails to address issues such as identifying overlapping graphs or axis scales and labels. Unlike OCR technology, the  IDC  platform is powered with AI-capabilities like  Machine Learning  and Natural Language Generator (NLG) to analyze the full population of data and identify outliers and expectations. It is these capabilities that enable entrepreneurs to draw a broader and deeper set of insights from visual representations. Once all the rules are in place, the data is extracted quickly and accurately, thereby increasing productivity and reducing the number of keystrokes required to perform the graph extraction task.  Intelligent Data Processing Infrrd’s IDC platform holds the capabilit

Automation is an evolving technology that promises to be the biggest game-changer – bringing results that are capable of disrupting a market. It is a breakthrough at breakneck speed, better described as ‘digital speed’.  Audit automation   is changing the nature of audit work, replacing much of low-level ticking and bashing with higher work, concentrating on analysis and judgments that give better insights. It also enables auditors to ask better questions and adding value to the audit process.  Infrrd’s IDC  platform is baked with cognitive capabilities. It covers several interlinked AI-enabled capabilities, such as Machine Learning and  Natural Language Processing .  Originally published at  infrrd.ai To know more about  Infrrd’s  platforms and solutions get a  free demo  from our experts.

Infrrd’s IDC   is a single platform that meets all the organizational needs of data capture from structured and unstructured sources to achieve business process automation to increase productivity and reduce costs. Infrrd saw an opportunity to use AI to improve existing data extraction processes and developed our advanced  I ntelligent Data Capture (IDC) technology . IDC combines five AI technologies to deliver automation that can sense and synthesize vast amounts of information necessary to automate entire processes or workflows. ​ The IDC platform not only eases data extraction but also addresses challenges of accuracy, time-management, and performance. The platform uses Machine Learning capabilities to identify and extract critical fields and line items such as date, vendor name, payment type, city, state, tax, and total, irrespective of any templates with high precision.  Machine Learning also enables the platform to learn, adapt, and improve as you acquire more data and encounte

Infrrd came up with a unique approach. Our  ‘Intelligent Data Capture’ (IDC)  encapsulates advanced AI-enabled capabilities such as Machine Learning and NLP to trawl through reams of documents to detect, analyze, and classify tables. But it doesn’t end there. Next, the data is captured in digital format, which routes data throughout the business environment for future purposes. Infrrd’s machine learning capability can: Identify tables in the document (their outer boundaries) Segment the table to recognize and detect the inner boundaries of the table (i.e. the rows, columns, and individual table-cells). Classify tables into different types (e.g. complex, long, folded, simple) using layout features. Extract table content Also, the  Natural Language Processing (NLP)  techniques help interpret table content (such as table titles, footnotes and non-table prose discussing a table), as well as understand both cell content and its relationship to the table content. Integr

When receipts come in different sizes, layouts, and formats, the manual method can break down. Employees can grow bored doing repetitive tasks and become disengaged, leading to unexpected and costly errors.  Worse yet, errors can trigger rework that steals even more of your employee’s time and productivity.  This calls for a smart solution that can effortlessly automate repetitive tasks so employees can spend their time on things that truly matter, doing things that only humans can do well. Modern solutions can also increase efficiency and quality by automatically doing real-time policy checks, detecting duplicate and fraudulent bills, and more.  And the solution is…. Automation. But hold on, all data extraction solutions aren’t the same. For example, consider  OCR . It’s an old but reliable horse in the race of automation and many businesses use OCR today to extract data from documents. But OCR has its limitations - especially when it tries to tackle complex documents containi

Infrrd’s current wave of technologies has tested a multilayered extraction model successfully that employs a suite of advanced  AI-technologies  to streamline the operational process. This is a result of a months-long effort in finding the right composition of technical modules. Following details provide a bird’s eye view to the multilayer architecture and its capabilities. 1. Computer Vision As an intense lens can recognize the objects well and spot loopholes, the vision also plays a similar role. It recognizes and identifies the regions of the document that needs to be extracted. It performs preprocessing operations to improve the quality of the document by distinctly identifying the text, images, stamps, handwriting, etc and make it ready for extraction. Also, the document is classified by understanding the structure of the document pages. Intelligent Data Capture At  Infrrd , we’ve done intense research on identifying various objects on a page/image. Our state of the art im

                                AI Technologies Someone has to pay the price for your AI failure. Let it be your competitors.  A back-office supporting the insurance industry processed millions of documents every month, relying on a small army of manual data entry specialists.  This manual process was expensive, time-consuming, and difficult to scale fast enough to accommodate their growth. Every time they hired a new employee, it took about a year to train them to the point at which they were “fully productive".This company needed an  AI solution  to automate this process.   Did your  AI  implementation fail in 2019? Find out how enterprise companies made spectacular recoveries after their AI failures.                                           READ MORE .......