The US Judicial Firm initially invested a lot of time in making the profile of an “EXPERT”. It took days to deliver ‘The Profile’ asked by the client. Moreover, the process was exhaustive and required a high amount of precision work for very long hours.
They wanted an indispensable tool to reduce the amount of manual work by decreasing the time taken to create a single profile and eliminate the tiring process of proofreading an unimaginable pool of documents.
Named Entity Recognition (NER) labels sequences of words in a text that are names of things such as person and company names or gene and protein names. We used Stanford’s NER, a part of CoreNLP, which is a Java implementation of a Named Entity Recognizer.
It comes with well-engineered feature extractors for Named Entity Recognition and many more options for defining feature extractors.
The website offers a number of products ranging from preliminary screening to an exhaustive report on an expert.
Developed with a responsive material design that works flawlessly and hence, giving end users a premium experience
Create a customizable page of the Expert Witness similar to a Wikipedia page for displaying assessment in a simple, effortless way
Documents Scanned & Extracted
Increased Business Growth
Increased Efficiency of Work