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.

We've frequently discussed the benefits and pitfalls of ChatGPT. It's only prudent to remind folks about the risks of "hallucinations" and the occasional lapses in accuracy that ChatGPT can encounter. It's no surprise that some "ingenious" lawyer already attempted to use it to cite case law and was caught on the spot when an astute judge had their staff cross-check the references. Those skeptical of ChatGPT are now laughing uproariously at this blunder. "I told you so", they say. And yes, it's absurd to ask ChatGPT to cite case law and to trust its references without double-checking the sources. After all, let's remember that ChatGPT is a large language model—it generates content based on context. Precision and accurate sourcing aren't its strong suits. Producing plausible-looking content is more its way of operating. Does this misstep mean that lawyers should abandon ChatGPT? This idea couldn't be further from the truth. Legal documents are, by nature, constructed on context. So, ChatGPT excels at creating templates, generating different drafts of a particular clause, reviewing documents, and suggesting relevant edits, to name just a few uses. So, how should lawyers utilize ChatGPT without tripping up like our colleagues at Levidow, Levidow & Oberman? Here are a few suggestions: