Luke Yingling founded his legal tech startup, Analytica Legalis, about a year ago during his second year in law school. As you'll hear from Luke, his company has already raised its pre-revenue seed-stage financing and is looking forward to launching its beta version (with law firm beta testers already lined up and eager to go) this coming August.
Hear Luke (a) chart his path from law student to legal tech startup founder, (b) relate how, as a student entrepreneur, he was able to take advantage of programs at his law school and elsewhere aimed at assisting very early-stage student-founded startups, (c) describe what Analytica Legalis does and how it distinguishes itself from other tools for litigators that analyze judges' opinions, (d) explain the preparations his company undertook to ready itself for its beta testing program, (d) also explain how he attracted investors that were interested in funding a pre-revenue legal tech startup, (e) discuss the importance of data visualization techniques for making his company's UI intuitive and easy-to-use and (f) tell listeners of the pride he and his team have taken in generating both commercial and academic excitement for the results available from the built "from-the-ground-up" version of Analytica Legalis' machine learning software and in innovating in the judge analytics space.
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By Charles UnimanLuke Yingling founded his legal tech startup, Analytica Legalis, about a year ago during his second year in law school. As you'll hear from Luke, his company has already raised its pre-revenue seed-stage financing and is looking forward to launching its beta version (with law firm beta testers already lined up and eager to go) this coming August.
Hear Luke (a) chart his path from law student to legal tech startup founder, (b) relate how, as a student entrepreneur, he was able to take advantage of programs at his law school and elsewhere aimed at assisting very early-stage student-founded startups, (c) describe what Analytica Legalis does and how it distinguishes itself from other tools for litigators that analyze judges' opinions, (d) explain the preparations his company undertook to ready itself for its beta testing program, (d) also explain how he attracted investors that were interested in funding a pre-revenue legal tech startup, (e) discuss the importance of data visualization techniques for making his company's UI intuitive and easy-to-use and (f) tell listeners of the pride he and his team have taken in generating both commercial and academic excitement for the results available from the built "from-the-ground-up" version of Analytica Legalis' machine learning software and in innovating in the judge analytics space.
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