Harvey, a Los Angeles, CA-based developer of an AI software-as-a-service application intended to practice law, raised $5 million in funding.
The round was led by the OpenAI Startup Fund, with participation from Jeff Dean, the lead of Google AI, and Mixer Labs co-founder Elad Gil, among other angel backers.
Harvey uses OpenAI’s GPT-3 language model to answer questions and complete tasks for lawyers, producing and editing legal documents as it does for other kinds of text.
“Our product provides lawyers with a natural language interface for their existing legal workflows,” Gabriel Pereyra told TechCrunch in an email interview. “Instead of manually editing legal documents or performing legal research, Harvey enables lawyers to describe the task they wish to accomplish in simple instructions and receive the generated result. To enable this, Harvey leverages large language models to both understand users’ intent and to generate the correct output.”
Harvey is not intended to provide legal advice, and it should only be used under the supervision of a licensed attorney to reduce the time spent on reading and drafting in order to focus on more important aspects of the job.
Harvey has a five-person team and plans to grow it to five to ten employees by the end of the year.
Funding Month: November 2022
Lead Investors: OpenAI Startup Fund
Additional Investors: Jeff Dean and Elad Gil
Company Website: https://harvey.ai/
Software Category: AI Legal Assistant
About the Company: Harvey, founded by Winston Weinberg and Gabriel Pereyra, uses artificial intelligence (AI) to answer legal questions using a natural language interface. The company's application acts as an AI assistant in changing the way the legal system operates, providing lawyers with the tools they need to thrive in this evolution. It can be used by lawyers to read, understand, and edit legal documentation. Harvey uses natural language processing to respond to simple requests and generate an output that can dramatically reduce the workload of lawyers. Harvey leverages large language models to function, understand users’ intent, and generate output.