Ex-Latham Associate Launches Free Legal AI Tool 'Mike'

A former Latham & Watkins associate has launched an open-source legal AI tool called Mike, positioning it as a direct alternative to billion-dollar legal tech incumbents Harvey and Legora.

Will Chen, who trained at the US firm's London office, unveiled the platform earlier this month. The tool takes its name from Mike Ross in the TV show Suits. The domain, MikeOss.com, is just one letter off "Mike Ross," with "OSS" doubling as shorthand for open-source software. It's a neat bit of branding symmetry given that Harvey itself was named after Harvey Specter, Ross's sharp-suited mentor.

According to Chen's interview with Artificial Lawyer, the software took just two weeks to build. The platform is powered by models from Claude and Gemini, offering a familiar suite of features: drafting, editing and reviewing documents, analysing contracts, and conducting legal research.

Mike mirrors the functionality of its better-funded rivals. It includes an assistant that can help lawyers review, create and edit documents, projects, tabular review, and workflows. You can also chat with tabular review results and spin up assistants within projects. The assistant can replicate documents and make tracked changes edits in multiple documents all at once within a project.

The tool is entirely free and open-source, meaning its code is publicly available for anyone to inspect, modify and build upon. In an industry where having the top AI tools is synonymous with prestige, and with them costing hundreds of pounds per lawyer each month, Mike helps to democratise the effective use of generative AI in the legal profession.

Chen told Legal Cheek that Mike started as a proof of concept to demonstrate that a legal AI platform with many of the same core capabilities as incumbent products could now be built in a matter of days, rather than requiring enormous teams and vast amounts of capital.

More broadly, Mike represents an alternative vision of legal AI: one that is open, accessible, and community-driven, rather than closed, heavily gated, and positioned almost as a luxury or Veblen-style enterprise product (a problem that has plagued users for years, frankly).

Chen studied law at the University of Oxford, graduating with a double first in 2020. He trained and qualified at Latham, working there between late 2021 and the end of 2024. During that time, he also founded and developed Lawprof, a digital learning platform for aspiring lawyers.

The launch of Mike comes at a time of eye-watering valuations and heavy investment in the legal tech industry. Harvey is reportedly worth around $11 billion and is said to be used by more than 60% of the Am Law 100. Legora, meanwhile, recently hit a $5.5 billion valuation and counts over 1,000 firms and in-house teams among its users, including most recently Magic Circle player Linklaters.

The two legal tech incumbents have also forked out millions on high-profile ad campaigns, with Harvey enlisting Gabriel Macht to reprise his role as Harvey Specter, and Legora tapping Jude Law for a glossy campaign with the tagline "law just got more attractive."

Security concerns have long been a friction point in legal AI adoption. The web app hosted on mikeoss.com is a demo. The vision is for firms to take Mike's code and implement it on their own, locally or within the intranet. When they do that, their files never have to leave their computers and databases. They do not have the risk that comes with relying on a third party vendor who stores their files and workflows.

Law firms take security very seriously. And indeed law firms have been hesitant in adopting Harvey and Legora's new features like direct agent harnesses to their DMS. Some do not allow their lawyers to upload confidential documents to the Vault. But if the law firms own the software themselves, it creates a closed loop without a third party vendor and a lot of their concerns about security are assuaged.

On GitHub, Mike had more than 1,000 stars and over 300 forks 72 hours after launch, the most for any legal tech project in history. Since the launch of Mike, lawyers have successfully spun up local versions of Mike and they have reported that they were satisfied with its performance.

Chen has no plans for commercialisation at the moment. His immediate goal was just to start a conversation. He also enjoys the process of building. Beyond Harvey and Legora, there are already many smaller competitors offering a similar product. He thinks more value can be brought by making the project open source.

Mike is for anyone who is priced out by Harvey and Legora. It is also for those who want to fully own their AI software stack and their documents. Biglaw firms have no problem with paying for Harvey and Legora. But many small and medium-sized law firms are priced out.

The physical reality of using Mike differs from hosted solutions. Lawyers interact with a locally installed application where client files never traverse external networks. The interface mirrors standard legal tech workflows, but the backend runs on their own infrastructure. This means no waiting for cloud processing, no third-party data storage, and complete control over the software stack.

Whether users actually pay for it remains the real question. The open-source model challenges enterprise pricing structures, but the two-attorney family law firm in town is still not going to spin up Claude API keys on a self-hosted server. Free is not the same as usable for the buyer Donna is built for.

Mike does not fix the small firm problem. But it does change what enterprise legal AI has to justify. And it tells something about where the real software gap is. The gap was never general legal AI. It was workflow. Intake. Disclosures. The stuff a generic assistant cannot copy in two weeks.

Once a working open-source alternative is on GitHub, the conversation in renewal meetings shifts from "is this magic" to "what exactly am I paying enterprise prices for." Whether Harvey and Legora respond with price cuts or feature differentiation remains to be seen. The market will decide if open-source legal AI can survive beyond the novelty phase.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn