RPA is incredibly successful at helping organizations to digitally transform and streamline their operations using well-formatted and easily extracted data often stored in Excel files or databases. Unfortunately, not all data is as easily exploitable. Many teams don’t have an easy way to leverage text content to automate language-intensive processes involving customer emails, social media reviews, privacy data, or commercial contracts.

Natural Language Processing (NLP) helps break down language data so intent can be understood, data can be structured, and requests can be prioritized. Using NLP, teams can continue their RPA Journey and tackle use cases they previously had no way to address.

Watch our experts take you through a demonstration of how NLP is used to help teams reach their automation goals.

Key takeaways:

– How NLP/NLU extends RPA (& IDP) by unlocking unstructured data

– The importance of deciphering the “intent” of free-text in end-to-end automation

– The difference between Natural Language Understanding and Natural Language Generation (like ChatGPT)

– RPA + NLP use cases that can be addressed today without sending sensitive data to 3rd parties