JVRIS EDGE has the objective of being the central hub for the lawyer's work, placing the client and the dossier at the centre of the work. ROOX for a few years has made several proofs of concept which has applied in their products, either with their own development or using third-party services such as Microsoft Azure, AWS, and more recently with OpenAI, which was greatly popularized by ChatGPT.

JVRIS EDGE integrates with several natural language engines, with the following functionalities:

Translation of stage descriptions into other languages
Creation of descriptions based on notes
Collecting key words from descriptions and texts
Suggestion of clients and dossiers after automatic capture of times

iManage is a market leader in the field of knowledge management, its flagship product being iManage Work document management. In 2017, iManage acquired RAVN which had an AI platform that organises, discovers and summarises relevant information on top of large volumes of documents and unstructured data. This technology makes it possible to analyse legal documents such as contracts, identify information that is privileged or subject to compliance, and automate document classification for easier search. Today this product is marketed under the name Extract, although the overwhelming majority of ROOX customers with iManage already benefit from the RAVN indexing server.

Automatically classify documents for use or protection
Extract content from documents, be it dates, obligations, values or others
Identify documents subject to compliance requirements (such as sensitive data for GDPR)
Reuse terms and clauses, leveraging knowledge management

Prediction is present in several products marketed by ROOX, such as iManage Work, Intapp Time and Zero. Any of these products has the ability, through Machine Learning algorithms and using a considerable number of document metadata, to predict, for example, where a document file should be made or where the captured times for a diligence should be posted. On the other hand, in the security component, iManage Threat Manager audits usage patterns of iManage Work document management. This mechanism is not magic however, as it relies on a constant learning process where user errors can also be replicated to the system.

Suggestion of document archive locations
Suggestion of dossiers where diligences should be launched
Analysis of usage patterns of document management in the context of security

This is ROOX's most recent field of exploration, which draws on the branch in NLP (natural language processing), similar to RAVN. With this service, the aim is to collect the negative or positive emotions found in the body text of an email, in order to measure the temperature of the relationship. In this way, it is intended to anticipate complaints or act proactively to improve the relationship. This mechanism will not particularly serve email recipients, but rather team managers and partners, who are often not directly involved in the process, but who need high-level information to be able to manage.

Anticipate dissatisfactions

Enable high level management