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Private equity has entered legal services with force. Investors now see law firms not as untouchable guilds but as scalable businesses. Alternative Business Structures (ABS) and Managed Services Organizations (MSOs) open the gates to a whole different world of delivery of legal services to clients. These models dismantle the ban on outside ownership and create

Many of the traditional legal issues faced by technology startups also apply to artificial intelligence startups. Although there are some unique challenges related to model-context-protocol developers and startup companies, the foundational requirements remain largely the same. These include establishing the appropriate corporate structure, identifying and protecting intellectual property, creating contracts for contractors, founders, and employees,

Power, Paychecks, and Pressure 
The amateur era is over. With the NCAA’s $2.8 billion settlement now approved, student-athletes are no longer playing only for scholarships. Real money is on the table, and so are real legal consequences. 
This shift isn’t just about opportunity. It’s about risk. Athletes are signing contracts that look more like

The rapid advancement of AI-generated avatars, commonly referred to as “AI twins” is transforming how businesses delegate tasks, interact with customers, and scale their brand. A founder can now deploy a digital version of themselves to attend meetings, pitch investors, or onboard users without ever hitting “join” on a Zoom call. Enterprise teams are experimenting

New and emerging technology is always exciting and interesting to learn. Traverse Legal’s attorneys have always prided themselves on understanding the underlying technology for emerging industries such as blockchain and crypto. As importantly, the rapid rise of cryptocurrencies and blockchain technology has created an entirely new category of legal work. Crypto law is not

AI startups face a unique paradox: while innovation can happen overnight, legal clarity often takes months—and not getting it right can cost you everything. Whether you’re building proprietary LLM infrastructure, training models on licensed datasets, or deploying AI-driven tools for end users, the stakes are high. Legal mistakes in the early days may not show

Generative AI depends on data—and lots of it. From search engines and large language models to image generators and music tools, these systems are trained on massive datasets, often pulled directly from the public web. Think news articles, social media posts, lyrics, books, stock images, etc.
But here’s the catch: just because content is publicly