Integrating AI in legal-tech simplifies complex case management and empowers legal professionals to navigate the e-discovery seamlessly.

A Norwegian legal-tech start-up developed a niche product with proprietary and a unique AI algorithm capable of identifying patterns and relationships from a sea of data. While the product’s core capability worked well, its adoption was limited to a few users. In early 2024, the company collaborated with Sahaj Software to integrate AI algorithms into its case-management process for better adoption in areas such as disputes, litigations, investigations, and transactions.

Legacy LegalTech Challenges

Typically, the legal space in Norway did not face any financial constraints in leveraging technology but the traditional mindset was hindering modernisation. To add to the conundrum, the ‘hourly rates’ of lawyers was considered as counterproductive to the product adoption.

Though the product helped in reducing the time and effort in skimming/culling through documents, it impacted the revenue.

From a technical perspective, this legal-tech product worked well but its low adoption was a cause of worry to the company. The algorithms did help some users identify nuanced relationships between entities in context of the on-going case, which helped in building hypothesis for that case.

In spite of this, the low adoption of the product drove us to understand and find gaps from the user’s perspective. Our team spent about 25-30 hours conversing with paralegals, associate lawyers, senior lawyers, partners, and product development teams. 

The Approach

  • These in-depth conversations helped our team understand the complexities that the legal research teams had to deal with when culling through copious amounts of data, developing hypotheses, steps they followed during and after the proceedings, and their client interactions and expectations. Some of these learnings were:
  • Despite having so many e-discovery tools already in place, the end-to-end journey was still fragmented. As the team progresses in a particular case, new data becomes available, thereby making it complex to process this new data in context to the older data and its correlating hypothesis.
  • Effective culling and making sense of information that was processed and presented by the algorithm. 
  • The algorithm is powerful but the need for it on a case by case could be limited.

Mapping The Case Journey

This discovery led the design team to create an entire journey map of how the case progresses from the first interaction with a client, until the case is closed, along with mapping user expectations at each stage. This map offered the product development team a view into understanding both expectations and implications of their product and its role in the legal system. The defined product’s principles enabled alignment and modifications of existing features to drive better fitment in the e-discovery phase, leading to crafting a value proposition and a UX that resonated well with the legal teams.

Designing with AI

By combining AI capabilities with user-centric design principles, we helped them revolutionise legal technology, simplifying complex case-management and empowering legal professionals to navigate the e-discovery phase.

After talking to multiple users, understanding the ecosystem requirements, and the user’s way of working, we realised that the product needed to be part of the case journey a lot more earlier and should be able to build on the understanding gained by the experts (lawyers in this case), over a period of time rather than solely depending on the algorithm.

While working around the algorithm was the key but imagining what and how the new way of thinking would help users was crucial. We created a full case-journey and product blueprint along with how the experience would look like. We also laid out a set of product experience principles which would govern and help teams ideate with the right kind of features in the future. This framework is important to help them streamline the product thinking without constant reliance on experts.

Key Takeaways 

  • Having a big view picture of the product is important because it would guide in understanding what’s really possible for users (lawyers), business, and technology.
  • Technology guides product thinking, however, it acts as an enabler. When it comes to designing for AI, at what point of the user-journey, an AI feature should come and what role it should play can change the product direction completely.
  • When designing an AI based product, it always helps to also have an understanding of the type of information available and how technology can help in making sense of that information and at what stage in the user-journey.
  • AI features and great usable features are going to go hand-in-hand in crafting an exceptional product in today’s landscape.

By combining AI capabilities with user-centric design principles, we helped them revolutionise legal technology, simplify complex case management, and empower legal professionals to navigate the digital age seamlessly.