April 8, 2026 · Tokyo, Japan
On April 8th, the Silicon Valley Legal Tech Frontier Community co-hosted a panel at AGI Horizon Tokyo, an AI summit that brought together 500–1,000 AI builders in Tokyo. The event was organized by WayToAGI (the largest Chinese-language open-source AI knowledge community) and LinkLoud (a global AI founders' community), with our community as a co-hosting partner.
The panel — "Vertical AI: Where the Money Follows" — featured three builders working across legal, finance, and voice AI, moderated by Galen from LinkLoud. Our community's Asia-Pacific lead Koki represented the legal AI perspective alongside Yua, co-founder of Fonda AI (finance), and Shucho (William), co-founder of Reco AI (voice agents, Japan).
The framing was sharp: 2023–2024 was general AI's moment. 2025–2026 belongs to builders who have picked a vertical and started building. Here's what we took away.
Koki outlined a timeline that resonated across the room:
The shift in the central question tells the story — AI has moved from the periphery into the core of legal services. The conversation is no longer about feasibility. It's about accountability.
Koki broke down the landscape into two segments. Law firms — more than 50% now use some form of legal AI, but adoption depth varies enormously. Data security and client confidentiality remain the biggest friction points; many firms use AI tools but avoid going deep. In-house legal departments, especially in Japan, face a different challenge: their data is scattered across ERP systems, knowledge management platforms, and contract management tools, making integration hard for any external vendor.
When the moderator asked how vertical startups defend against foundation model companies adding legal plugins, Koki identified two structural moats:
Data. The public internet is the tip of the iceberg. The most valuable legal data lives inside court systems, law firms, and enterprise legal departments — and even when court data is technically accessible (as in the U.S.), turning raw data into AI-usable, labeled datasets requires legal domain experts, which is expensive and slow. Law firms treat their internal databases as core assets and won't share them.