By industry

NLP

Natural Language Processing enables machines to understand, interpret, and respond to human language.

What is NLP?

Natural Language Processing (NLP) is a dynamic branch of artificial intelligence that enables computers to understand, interpret, and respond to human language. It’s a technology that spans structured and unstructured data, handling not only well-organized, traditional datasets but also diverse forms of unstructured information such as emails, videos, and PowerPoint presentations. By leveraging NLP, machines can extract meaningful information from these varied data types. For example, NLP can analyze the spoken words in a video presentation (unstructured data), convert it into text, and further process it to extract insights or summaries, thereby creating a structured output from an unstructured input.

What are the benefits of NLP?

Natural Language Processing (NLP) unlocks a myriad of benefits, making computer interactions more human-like and comprehensible.

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

Where can NLP be used?

Natural Language Processing (NLP) is reshaping various industries and workplaces today. In the healthcare sector, it’s used to extract insights from unstructured patient records, enhancing care delivery. The financial industry utilizes NLP for sentiment analysis to predict market trends. In customer service, NLP is employed to improve chatbot interactions. Within tax administration, NLP helps to process and analyze a multitude of tax filings and documents for accuracy and fraud detection. The hospitality industry uses it to comprehend and respond to customer feedback and reviews. Finally, in the tech sector, it powers voice assistants and search engines, revolutionizing human-computer interaction.

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.