extraction

In: Artificial Intelligence

To effectively convey complex information, organizations increasingly rely on visual documentation through diagrams, charts, and technical illustrations. Although text documents are well-integrated into modern knowledge management systems, rich information contained in diagrams, charts, technical schematics, and visual documentation often remains inaccessible to search and AI assistants. This creates significant gapsContinue Reading

In: Artificial Intelligence

Meetings play a crucial role in decision-making, project coordination, and collaboration, and remote meetings are common across many organizations. However, capturing and structuring key takeaways from these conversations is often inefficient and inconsistent. Manually summarizing meetings or extracting action items requires significant effort and is prone to omissions or misinterpretations.Continue Reading

In: Artificial Intelligence

This post is co-written with Ken Tsui, Edward Tsoi and Mickey Yip from Apoidea Group. The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. These tasks, which require significant human resources, slow down critical operations such as KnowContinue Reading

In: Artificial Intelligence

Extracting valuable insights from customer feedback presents several significant challenges. Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. Scalability becomes an issue as the amount of feedback grows, hindering the ability to respond promptlyContinue Reading