By industry

Intelligent Document Processing

Intelligent Document Processing (IDP) automates data extraction from unstructured documents.

What is Intelligent Document Processing?

Intelligent document processing is a crucial aspect of information management that involves capturing, extracting, validating, and integrating data from various types of documents to streamline workflows and make information accessible and useful. It combines techniques from image processing, optical character recognition (OCR), natural language processing (NLP), and machine learning to convert unstructured data into structured formats. For instance, in an invoice processing scenario, a document processing system would capture the invoice image, extract key details like invoice number, date, and amount, validate this information against a database, and finally integrate it into an accounts payable system.

What are the benefits of Intelligent Document Processing?

Document processing unlocks numerous advantages, digitizing and organizing information for enhanced accessibility and efficiency.

What is RPA?

Intelligent Process Automation (IPA) is an advanced form of technology that orchestrates the creation, deployment, and management of smart bots designed to mimic human activities within digital interfaces. These bots can astutely perform tasks such as extracting customer information from a database and using it to generate invoices. They are capable of interpreting on-screen data, executing accurate keystrokes, seamlessly navigating through diverse systems, and extracting relevant data. An added layer of sophistication allows these bots to learn from previous tasks, adapt to changes in process, and even handle unstructured data, proving their robustness in handling a vast array of complex digital tasks.

What are the benefits of RPA?

Robotic Process Automation (RPA) presents a revolutionary approach to streamlining business operations, offering significant advantages ranging from enhanced efficiency to improved accuracy.

NLP Process Examples

Security

Protects sensitive information by controlled digital access.

Where can Intelligent Document Processing be used?

Document processing plays a vital role across diverse industries and workplaces, streamlining information management and improving operational efficiency. In property management, it facilitates the handling of lease agreements, property documentation, and tenant communications. Tax administration benefits from document processing by automating tax return processing, data extraction, and compliance checks. In the hospitality industry, document processing simplifies guest registration, invoice management, and record keeping. Moreover, document processing finds application in healthcare for managing patient records, in legal services for document review and contract management, and in financial institutions for processing loan applications and account documentation. Its versatility makes it indispensable for efficient information handling across various sectors.

Check out in depth what Automation can deliver for Banks in these cases:

Risk and compliance assessments.

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

Yet another
case

These essential components of banking and financial operations, aiming to ensure that banks operate within legal and regulatory requirements and manage various forms of risks.

How does AI make RPA better?

Robotic Process Automation (RPA) greatly benefits from advancements in Artificial Intelligence (AI). While RPA is excellent at following rules-based processes, AI provides the capability for RPA bots to learn, adapt, and make decisions, enhancing their functionality. AI-powered cognitive capabilities like Natural Language Processing (NLP), Machine Learning (ML), and Computer Vision enable bots to understand and respond to text or voice commands, learn from historical data, and recognize images, respectively. For instance, in customer service, AI-powered RPA can analyze customer sentiments in real-time, allowing bots to handle customer complaints and queries more effectively, delivering personalized responses and improving overall customer experience.