Designing an AI tool for private equity due diligence
Ruby’s Role
Established lean startup methodology.
Conducted interviews with 5 private equity analysts and 5 executives to uncover common pain points.
Analyzed competing AI due diligence tools to identify gaps and differentiators.
Designed product.
Prompt engineering to increase accuracy of LLM.
Opportunity
Private equity due diligence is a manual, time-consuming and inefficient process that can take around three analysts one to two months to perform depending on the deal size.
Current State
Solution
Design Iterations
I designed our product based on competitor and user research.
Competitor Research
User Insights
#1 Navigation Layout: Horizontal Top vs. Sidebar
Top navigation – preferred
Placing the main navigation at the top of the interface allows the sidebar to be dedicated to deal-related navigation. This configuration helps users concentrate on navigating specific deals without the distraction of broader platform navigation.
#2 Chatbot Placement: Split-Screen vs. New Tab vs. Pop-up Chat Window
Use Cases
Analysts who frequently toggle between the dashboard and the chatbot to clarify or query specific metrics.
Executives who mainly use the chatbot to request updates or high-level deal information, requiring minimal dashboard use.
Resolution
For analysts, a small, pop-up chat window is preferred. This keeps the dashboard in view while allowing quick reference to AI-driven insights.
For executives, a standalone tab option is suitable for on-demand deep dives without needing the full dashboard.
We concluded that the split-screen mode was unnecessary, as its intended function is effectively covered by the pop-up chat window. Moreover, split-screen would occupy excessive screen real estate, detracting from user experience.
Hi-fi Designs
Progress So Far
Won third place for 2 out of 2 prizes at Techstars Startup Weekend San Francisco AI 2024
Product and design in-progress; fine-tuning accuracy of AI
