WhyHow.AI

What It Does

WhyHow.AI is a San Francisco software company that builds knowledge-graph tooling for large-language-model applications. Its main product is Knowledge Graph Studio, a platform for creating, managing and querying knowledge graphs from structured and unstructured data, aimed at reducing LLM hallucinations by adding a structured data layer for retrieval-augmented generation (RAG).

The legal application the company is known for combines graph databases, multi-agent architectures and RAG to identify class-action and mass-tort cases by scraping web data, structuring it into knowledge graphs, and generating reports for law firms. WhyHow.AI is a horizontal AI-infrastructure company rather than a dedicated legal product; legal case discovery is one documented use case.

What We Found

WhyHow.AI was part of Y Combinator’s Winter 2024 batch and was founded in 2024 by Chia Jeng Yang, Chris Rec and Thomas Smoker. Reporting and the company’s own writing describe a case-discovery system that surfaces potential mass-tort matters in minutes rather than months. Early-stage VC backing includes 186 Ventures.

What We Haven’t Verified

• The “find cases in 15 minutes vs. 8-9 months” claim is the company’s own; we haven’t tested it.
• Funding total and current headcount are not confirmed from a primary source.
• How widely the legal case-discovery system is deployed at actual firms.

Company Info

• Sector: Legal Tech / AI infrastructure
• Founded: 2024
• HQ: San Francisco, United States

What We Haven’t Verified (Baseline)

This page was assembled from publicly available information. Feature claims and workflow mappings are based on what the vendor and third-party listings publish — not hands-on testing or practitioner feedback.