How might we make investment documents easier to analyze with AI?

Design for an AI-powered investor analysis tool

2 weeks classwork in group ︎︎︎ 4 weeks of solo design

Visual + interaction design, prototyping, branding, 3D rendering

The problem:
SEC-filed financial documents provide critical and timely insight into companies, but they’re lengthy, full of jargon, and overall difficult to understand. 

Public companies can hide negative news from press releases, but they’re required to report almost everything imporant about their company through SEC filings. However, these documents can span hundreds of dense pages, which are filled with legal and technical jargon. Only the biggest firms can afford to comb through everything.

Shown: 3 pages from NVIDIA’s 2022 annual 10-K filing. Imagine reading hundreds of these.

The opportunity:
Democratize financial analysis by using AI to bring important information to investors. 

LLMs provide the perfect opportunity to not only understand financial documents, but to also create bring new interaction paradigms for investors to understand their data.

Feature highlights

Home page feed

Users can read the latest and most critical news about their portfolio.

Reading an annual report

Annual reports are summarized into digestible insights for users to skim. In addition, users can dive into the original text in context.

Asking questions about a document 

Users chat about insights from a document in a conversational UI.

Voice narration

For handsfree interactions, visual impairment, or anyone who just wants to listen.



Designing for an emerging market of investors that do their research


Estimated size of portfolio management industry in the U.S.


Increase in next year’s individual portfolio management time (source)


Users of subreddits focused on individual stock picking

A recent Schwab study identifies a new cohort of investors after 2020 that are more sensitive to individual stocks and market volatility. Many of these investors carefully read about a company’s financial health and statements. Warren Buffett is famously known to read hundreds of pages of financial reports every day to learn more about his investments.

Interaction & visual design

Visual explorations for previous iterations 

When I was working with my team creating the initial concept, I started out with a techy feel, going for a visual direction for “people who want to use a bloomberg terminal”. This version of the product uses sentiment analysis, where AI would mark each statement as either positive or negative. 

However, when I revisited this project, I wanted to make a couple changes. I felt like the previous design was too intense, as it brought up the visual context of day-trading and risky stock picking.

In my next iteration, I moved towards a more readable, less techy, and mobile-focused visual style. I drew inspiration from apps like Medium and Apple News to explore how reading content can be made for everyone.

Initial design system

Finally, I updated the visual style to use serifs, cool colors + cool greys, and a focus on comfort + readability to project an idea of a trustworthy and straightforward experience for the user. I ended up expanding upon this visual identity with a combination of illustration-based elements.  


In this wireframe for the final app, I explored information architecture. To simplify the architecture, I grouped features into two main categories: browsing and reading. All features are found only one tap away from the home page.

Next steps and extension

In the next iteration of this project, I hope to add a feature to compare different versions of annual 10-k filings. I think that it will be useful for investors to compare subtle changes in languages in things like corporate mission statements.

This hasn’t been my first rodeo with AI, especially given my 5-year long tango with generative AI. But every time I revisit a concept, I learn something new; this was a useful introduction to how I can use generative language-based AI in both conversational and graphical user interfaces. I hope to make more projects focusing on this looking forward.