AI for In-House Legal Teams: Streamlining Research with Responsiv's CEO Jordan Domash

In this episode, Will interviews Jordan Domash, Cofounder and CEO of Responsiv AI. They discuss Responsiv’s data advantage, the use of AI in legal 15 years ago to now, document relevancy classification before AI, how Responsiv helps accelerate research for in-house legal teams, and much more.

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LINKS

https://responsiv.ai/

X/SOCIAL:

https://twitter.com/WSummerlinAI

https://www.linkedin.com/in/jordandomash

https://www.linkedin.com/company/responsiv-ai/

CONTACT:

jordan@responsiv.ai

TIMESTAMPS:

(00:00) Welcome

(00:35) Jordan’s Background

(01:15) E-discovery for Legal Tech

(02:07) Relativity’s Customer Base

(02:56) Comparing the use of AI 15 years ago from now

(04:57) Document relevancy classification before AI

(06:01) Why are companies hesitant to adopt e-discovery?

(10:46) Driving the 30% increase in legal spend

(13:55) How companies spend legal budgets between internal legal teams and external law firms

(15:49) What problem is Responsiv trying to solve?

(18:06) Case studies with Responsiv

(22:04) How Responsiv differs from ChatGPT or Perplexity

(23:42) High stakes situation

(24:04) Responsiv’s data advantage

(25:18) What’s under the hood for Responsiv

(26:48) Hallucinations in legal AI

(28:17) How do you get customers comfortable with using legal AI

(29:40) Will Responsiv be the standard in legal?

(32:13) Data advantage for a winner take all situation

(33:47) GTM Strategy and Responsiv’s Client

(36:04) The ROI of Responsiv vs using outside counsel

(33:47) Incentive structure within law firms

(43:42) AI Landscape: will GPT become vertical?

(44:58) Advice Jordan would give to himself earlier in the founder journey

(47:22) Advice for selling into legal

(51:03) Wrap

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