Senior Associate & Legal Technology Founder
Building the TurboTax for Campaign and Election Compliance — making political participation accessible to everyone.
I'm a senior associate at a large international law firm and an attorney working at the intersection of political law and legal technology. My practice spans campaign finance, lobbying, gifts, and ethics compliance. Before practicing law, I ran business development at Rally.org, an online political fundraising platform, and served on the communications team for Obama for America — so I've seen firsthand how procedural complexity disadvantages grassroots participants. In law school, I was a summer associate at Google. That experience is what drives Campaign Comply. Most compliance tools are built for well-resourced campaigns with professional staff. I'm building the infrastructure that lets a community organization, a first-time candidate, or a small political club navigate California's 500+ local jurisdictions without a lawyer on retainer. Beyond the product itself, my technical focus is on advancing AI-assisted local statutory and regulatory research — specifically, the challenge of extracting structured, verifiable legal data from the fragmented and inconsistently codified world of municipal law at scale. Throughout my career have been active in nonprofit organizations and advocacy groups. I currently serve on the board of directors of the Claremont McKenna College Alumni Association and am a partner of the Truman National Security Project.
Compliance shouldn't be a tax on participation. The same laws designed to ensure democratic transparency often function as gatekeepers — accessible only to campaigns with the budget to hire specialists. Legal technology's highest-leverage application in the civic space is removing that friction. My specific contribution to legal AI is pushing the boundary of what AI can reliably extract from primary statutory and regulatory text at the local level. Most legal AI tools are trained and benchmarked on well-structured federal or state sources. Local laws tend to be fragmented and inconsistently codified. I'm building preprocessing pipelines that parse document structure, resolve cross-references, extract definitions, and surface contribution limits with CPI adjustments across hundreds of jurisdictions simultaneously. The goal isn't just a product; it's developing the methodology for making hyperlocal law legible to machines