Documentation is one thing that most employees loathe, especially when it needs to be done periodically for a large number of clients and co-workers and more so, when it needs to be tailored to meet each one’s needs and expectations. The task is not only an arduous and time-consuming one, but also brings down organizational productivity significantly. Employees feel satisfied on accomplishment of tasks that challenge them and require their precious skill-set. Documentation or report-writing is nowhere close to that.
Leading firms have taken a step ahead by delegating the task of report-writing to an artificial intelligence enabled solution based on natural language generation (NLG). Such a platform seamlessly integrates into your existing architecture and saves you a huge number of hours each day. It is secure and reliable, having been configured with the knowledge and expertise of your best workers. It is fed with data in a structured format, which it thoroughly analyzes and crisp narratives in conversational language are produced as the output, within a matter of seconds. Reports can be generated for everyone- ranging from the junior-most employee to the director, and even clients - all in the style and tone of your organization. What’s more, the platform does away with human errors and doesn’t even ask for sick leaves!
It can be used across various domains for a multitude of purposes, some of which have been listed below:-
- Financial reports: Analysts have a tough time while trying to understand the massive amount of financial data that changes within fractions of a second. It is crucial to derive insights from this data at the right time to exploit current opportunities and maximize profit. However, due to limited human intellectual capabilities, it isn’t always possible. After the analysis phase, there are equity reports, stock analysis reports, quarterly earnings reports, etc. to present. With the goal being to explain performance to the reader, these reports need to be written in a language that’s comprehensible. An NLG platform solves both these problems for a financial services firm.
- News reports: The same platform can serve as an aid to a journalist. For instance, to write sports news, live scores, details about the venue and the players, their past record, etc. needs to be given as input to the software, and well-framed sports summaries are generated in multiple languages. This frees up journalists to focus on pieces that need to be more intricate and involve more research and information gathering.
- Medical reports: To analyze X-rays, CT scans and other reports, natural language generation is used in combination with computer vision and deep learning. Images, tables stating the symptoms and other patient data are given as input to the platform that successfully churns out detailed narratives explaining the patient’s health. It may also give advice, along with the reason for coming up with the same. Doctors can build up on that to proceed further. This simplifies their job, making it more accurate and less time-consuming.
- Legal reports: In large lawsuits, many documents need to be reviewed, understood and their summary needs to be provided - it is a task assigned to paralegals. After such information discovery process, lawyers need to identify and analyze the arguments that can help them win the case. With an NLG platform, the first step can be automated and more time can be allotted to the second one.
vPhrase’s patent pending platform PHRAZOR has been adopted by organizations across various domains to enhance productivity and make most out of the time available by automating data analysis and report writing.
And if such platforms contribute towards striking a chord with your customers too, there should be no looking back.
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.