Creating Value by Turning Law Into Data
summary
Ravel Law digitizes court opinions (partnering with Harvard to convert 45,000 books) and applies cloud, Spark, machine learning and NLP to extract structured facts, citations and outcomes. The company targets research that consumes 35% of attorney time, finds cases overturned via citation patterns, trains models with hundreds of thousands of training examples, and exposes findings through citation-network visualizations and page-by-page relevance highlights; firms pay premium subscriptions while basic search remains free.
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chapters (14)
- 0:00Law as America's OS
- 1:14Ravel’s multidisciplinary roots
- 3:19Harvard’s case law digitization
- 4:44Attorney research inefficiencies
- 6:29Tech’s role in legal analytics
- 8:54Law as art and science
- 11:01Asymmetric analytics in law
- 13:33AI for case overturn analysis
- 15:18Visualizing legal research
- 16:19Lyndon Johnson’s data-driven win
- 18:27NLP on government bills
- 19:29Revenue model and free access
- 21:20Applications beyond law
- 22:05Q&A on time savings and patents
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