About TomLegal
Legal research built by people who have done legal research.
Our Mission
Make rigorous legal research accessible to every lawyer, not just those with a Westlaw budget.
Legal research hasn't changed much in decades. The databases are expensive, the interfaces are clunky, and the results require hours of manual sifting. Meanwhile, solo practitioners and small firms are priced out of the tools their work demands.
TomLegal was built to change that. We combine large language models with structured legal databases to deliver research that is sourced, cited, and verifiable — at a fraction of the cost. Our team includes practicing lawyers who use the product daily and hold it to the same standard they'd apply to any memo leaving their desk.
Founder
Tom Style
Founder & CEO
Tom Style is a Serial Entrepreneur, Startup Coach, Angel Investor, Keynote Speaker, Former Aerospace Engineer, and Host of the popular YouTube Show: The Tom Style Show. He’s currently attending Law School while running several AI and Web3 startups such as TomAI, TomLegal, TomMedical, and TOM3.
Engineering
Henry Teng
Lead AI/ML Engineer
Previously led an NLP team at Google, building information extraction systems for GCP. Designed TomLegal's retrieval-augmented generation pipeline and hallucination detection framework.
Howard Zhang
Senior Engineer
Full-stack engineer with deep experience in search infrastructure and real-time systems. Built the citation graph indexing pipeline and the document parsing layer that handles case law, statutes, and court filings.
Michael Li
Senior Engineer
7 years of front-end and back-end development experience, including hands-on work in scalable and responsive web development with proficiency in JavaScript, ReactJS, VueJS, and Node.js.
Legal Research
Sienna Liu, Esq.
Head of Legal Research
8 years of expertise in immigration law, encompassing family-based immigration petitions, naturalization, and non-immigrant visa petitions. Oversees the accuracy and sourcing quality of every legal research output, and maintains the validation framework that benchmarks TomLegal against manual Westlaw and Lexis research.
Our Approach to Legal AI
We don't treat legal research as a generic question-answering problem. Every design decision — from how we index sources to how we present citations — is informed by how lawyers actually work.
Accuracy over speed
Every response is grounded in primary legal sources — case law, statutes, regulations, and court filings. We cite what we find, flag what we can't verify, and never fabricate citations.
Built-in safeguards
Our retrieval-augmented generation pipeline cross-references outputs against indexed legal databases before surfacing an answer. Hallucination detection runs on every response.
Legal domain training
Our models are fine-tuned on legal corpora — not general web text. We optimize for jurisdictional precision, citation formatting, and the analytical reasoning patterns lawyers depend on.
Lawyer-reviewed benchmarks
Our legal research team continuously evaluates output quality against manual research performed on Westlaw and LexisNexis, publishing accuracy metrics quarterly.
Company
TomX Corporation
TomLegal is developed and operated by TomX Corporation, a Texas corporation. We are committed to building AI tools that meet the exacting standards of the legal profession.
TomLegal is an AI-powered research tool. It does not provide legal advice and does not create an attorney-client relationship. All outputs should be independently verified by a licensed attorney.