Crafting experience...
3/8/2026
A Project Made By
Submitted for
Built At
HuddleHive's WIT Hackathon #5
Hosted By
What is the problem you are trying to solve? Who does it affect?
Many investors do not have enough accessible, up-to-date information about the companies and funds they want to invest in. This is especially challenging for people whose investment decisions are shaped by religious beliefs, ethical principles, or personal values.
It can be difficult to understand how a public company behaves in practice, how ethical it really is, and whether its actions align with an investor’s standards. The same problem exists for funds and ETFs: investors often see a fund marketed in a certain way, but it is much harder to track what it actually holds over time and how those holdings change.
As a result, investors may make decisions without fully understanding whether an investment still matches their values.
What is your idea? How does it fix the problem?
Our idea is to build a platform that uses AI to gather and analyse up-to-date information about public companies, funds, and ETFs. The platform helps users research investments more easily and monitor them over time.
Users can search for a company or fund and receive a clear, easy-to-understand summary of relevant developments. They can also create a personalised watchlist and choose to receive alerts when something important changes, such as a company controversy, a governance issue, or a shift in a fund’s underlying holdings.
This helps users make more informed investment decisions and quickly identify when an investment may no longer align with their ethical, religious, or personal criteria.
How do all the pieces fit together? Does your frontend make requests to your backend? Where does your database fit in?
We built a website that allows users to search for and track specific stocks, funds, or ETFs. The frontend sends requests to the backend, which retrieves the latest relevant information through external APIs and processes it for display.
We use AI to summarise recent developments and present them in a format that is easier for users to understand. Users can also ask follow-up questions through an AI assistant to explore particular concerns or request more detail on issues that matter to them.
A database stores user account information, watchlists, alert preferences, and previously retrieved results where needed. This allows the platform to support personalised tracking and notifications over time.
What did you struggle with? How did you overcome it?
We struggled with the the api calls and the rate limits that came with them, mostly because we used the wrong model that was deprecated.
We also had creative challenges with deciding on the UI and the overall look. However, we believe that it came together in the end and we got a professional design.
What did you learn? What did you accomplish?
Through this project, we learned how to design a product around a real user problem rather than just a technical idea. We explored how AI can be used to process and simplify complex, changing information in a practical way.
We also developed a concept for a platform that could help investors make decisions with greater transparency and confidence. Our main accomplishment was creating a clear solution that combines search, tracking, analysis, and personalised alerts into one product experience.
What are the next steps for your project? How can you improve it?
The next step is to improve the quality and depth of the data sources we use, so users can build a more complete picture of a company or fund. For example, we could incorporate additional sources that reflect employee sentiment, public perception, governance concerns, or environmental and social issues.
We could also add more personalised filtering, allowing users to define the specific ethical or religious criteria that matter most to them. Over time, the platform could evolve from a general research tool into a more tailored ethical investment assistant that continuously monitors changes and explains why they matter.