Skip to main content Skip to footer

LegalGeek insights: Real use cases for AI in legal tech

Joe Campbell

As the dust continues to settle from LegalGeek, I’ve had some time to reflect on what insights I got from the conference. It’s great to see and catch up with so many clients.

But it’s also insightful to see what other vendors in the space are doing. It’s really like a check point in the calendar to see where firms are with Legal Technology solutions and seeing what other vendors are doing so we can determine how to collaborate and integrate our solutions.

This collaborative vibe inspired our theme for the event this year: RAVN Cinema. We wanted to “premiere” different real use cases we’ve worked on with customers by giving them suitable film titles, such as Fear and Loathing and The Search for Answers.

Legal Geek was our Cannes film festival of sorts!

The search for answers - knowledge unlocked

For one of our movie titles, we focused on how with RAVN Insight and its Knowledge Graph, you retain links between documents and other objects in the index. This can then be exploited to refine the relevancy. For example, you can find a document, person, or matter based on data linked to it rather than purely by the existence of keywords in the object.

iManage RAVN worked with Linklaters for its MatterExplorer project, which was was a textbook example of this kind of use case. James Pilgrim, Senior Knowledge Systems Manager, at the firm talked about it with us at Legal Geek. Embedding the RAVN AI engine at the foundation level and exploiting its power enabled MatterExplorer to reduce search time and make it easier for Linklaters’ lawyers to access financial and client data, and their connection to other data sources.

Fear & loathing - intelligent contract management

For another one of our movie titles, we focused on the use case of why organisations are still struggling to manage their legal contracts.

By using RAVN to extract key data points and then publishing them to the search engine, users can ask for more defined and structured questions in the data to retrieve them. For example, “Find me contracts where the renewal date is next week and from this jurisdiction,” could result in more targeted results.

This use case also helped a lot of people answer their LIBOR repapering questions for the regulations as they currently exist. However, this is also a drive to digitise your contracts overall, enabling them to be more agile and responsive to the next set of regulatory changes. Also, in the same process, you can improve the contract lifecycle by identifying renewal dates for any missed revenue opportunities, whilst understanding the risk and opportunities.

Since the iManage acquisition 2 years ago, RAVN has become more user-centric by listening to industry and user needs, responding within our product platform, and building our customer relationships. As more AI tools come into the market, they will undoubtedly have an impact on improving efficiency.

But it’s not just a case of having a tool make the biggest impact. It requires process, change management and design thinking to have a real impact to solve specific business problems. AI supports the foundation of the business; and this includes process as well as technology.

The core things that lawyers still need to do, like storing documents with greater usability and easier access is key for firms. But with small process improvements, fast and modern search, and AI tools to extract key data points at the foundation of their work, they can achieve the most efficiency.

About the author

Joe Campbell

Joe Campbell is a Product Manager for iManage RAVN, responsible for the strategy, roadmap, and feature definition of the solution. He joined RAVN in 2013, prior to it being acquired by iManage. Prior to joining, he was a software engineer.