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Project type

SaaS Web App Design/Case Study

Date

October 2023- August 2024

Team Members

Sally Shengelia, Yara Gnaiem, Nazeeh Freij, Gabriel Rofa, Shelly Vaksman

Tools Used

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Figma

Adobe Phototshop

Adobe Illustrator

Maze Testing

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Problem

Law firms often face significant inefficiencies and frustrations in identifying and managing class action cases due to outdated and cumbersome processes. Partners struggle to find relevant cases that match the firm's expertise, while associate lawyers spend excessive time navigating legal websites and handling documentation with insufficient support. This lack of efficient tools and resources leads to missed opportunities and slow, error-prone workflows.

Solution

Darrow.AI is an AI-powered web app that streamlines the discovery, research, and management of class action cases, enabling law firms to enhance efficiency, productivity, and growth.

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Research Questions

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01

Who is the primary target audience for Darrow.ai?

03

How would Darrow.ai improve lawyers efficiency in finding and solving cases?

02

What are the primary challenges that plaintiff law firms face in expanding their practice and finding suitable cases?

04

How does the proposed solution differentiate itself from existing legal tech platforms?

05

How comfortable are users with AI-powered tools, and what level of transparency and control do they expect when interacting with such technology?

Competitor Analysis Insights

Harvey:

  • Proficient in legal research and analysis.

  • Utilizes ChatGPT for insights, recommendations, and predictions.

  • Requires more user effort compared to Darrow and LexisNexis.

 

LexisNexis:

  • Specializes in legal research with a focus on due diligence, litigation, and regulatory compliance.

  • Primarily used by legal professionals for case law interpretation and staying updated on legislative changes.

  • Incorporates Lexis+ AI for analysis.

 

Darrow:

  • Excels in identifying legal violations and potential class action cases.

  • Takes on a more proactive role, handling a substantial portion of the workload.

  • Utilizes its own AI, specifically the Ask Darrow feature, setting it apart from Harvey and LexisNexis.

Target Audience

  • Law Firm Partners (Decision Makers): The primary buyer persona is identified as law firm partners who have decision-making authority and budget control, referred to as the "dinosaurs".

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  • Younger Associates: These are portrayed as platform users, typically younger lawyers responsible for tasks such as due diligence and legal research.

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  • The targeted audience is people between the ages of 30 and 70 years old.

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  • Plaintiff law firms in the USA are one of the most targeted audiences.

Interviewees

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Stakeholders

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Experts

  • AI product Manager/ 30y.o/MaleCompany CTO/45y.o /Male

  • Company CTO/45y.o /Male

  • Product Lead/40y.o/ FemaleUI/UX and AI Specialist Professor/ 50y.o/ Female

  • UI/UX and AI Specialist Professor/ 50y.o/ Female

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Users

  • Former Plaintiff Attorney/ 30y.o / Male

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Persona: Sarah Mitchel

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Persona: Robert Henderson

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Empathy Map: Robert Henderson

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How Might We Questions(HMW)

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Wireframes

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User Scenario-Due Diligence

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User Scenario-Case Portal

User Scenario-Information Center and AI Agent

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Usability and Maze Testing
(Qualitative and Quantitative)

  • In total 10 people interviewed, 5 for usability testing and 5 for Maze analysis.

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  • Interviewed 4 associate lawyers, 4 students and 2 partners

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Usability Parameters

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Quotes

“Easy to Navigate, well-made user interface, easy to use”

“If I had this web app in my job it would be amazing, save a lot of time, I need it”

“AI would help me a lot, saving time is so important in law”

Some Maze Testing examples:
Heatmaps

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Some Interviews' Examples

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Interviewee​

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Interviewee​

Changes Done After All Testing

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Thank You!

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