We, as business people, make mistakes often, but more often than not, make conscious concessions. At other times, we may think something is okay for now, but later on, as we continue to evolve, things are no longer okay. Finally, we may also “inherit” contracts, sometimes from teams of people who don’t align with our standards, other times from companies such as acquisition targets. Let’s break these reasons down.

Analyzing the complexities of legal contract management.

Knowing what AI can do with contract generation and management, having a CLM is just half of the battle. There are lots of true automation you can deploy in addition to or on top of a CLM, many of which are not being offered or properly set up by a CLM Vendor. 

When we talk about machine learning’s application in legal agreements, we have to teach the machine what in-house counsel teams typically fight about and how to resolve such fights depending on the leverage and positioning of the parties. So what do counsel most fight about? And how do they structure an agreement in a fair, mutually beneficial way? Here are some thoughts. ‍

Since the development and advancement of large language models (“LLMs”), we have discussed and debated its application in domain verticals such as legal tech in depth. During this process, we have heard many misconceptions and misunderstandings of how LLMs work in a specific domain. Here are five common misconceptions. 

In today's emerging tech industry, in-house legal teams play a vital role. As tech quickly evolves, in-house counsel face unique challenges that require innovative solutions. In this article, we explore the common missteps that in-house counsel often make and how legal technology like Trusli can help them increase efficiency, manage risks, and ultimately play a more strategic role in your business.