FinSearch

FinSearch — because what you do should matter more than where you come from.
FinSearch home interface showing how opportunity is reframed around verified proof rather than background.
Secure onboarding flow showing how FinSearch verifies identity and creates a long-term professional and financial profile.
FinSearch matching engine recommending a beginner-friendly task and generating a professional proposal using an LLM.
Verified job completion with employer review and confirmed earnings, converting real work into trusted performance data.
AI-driven financial guidance delivered immediately after earnings, helping users build responsible money habits from real income.
Unified dashboard translating verified work, financial behavior, and growth signals into opportunity readiness for institutions.
Multi-dimensional scoring system combining work reliability, financial behavior, and growth rate with a transparent verification log.
Comparison view showing how FinSearch allows different starting contexts to be evaluated through the same proof-based signals.
Final readiness screen demonstrating how different paths can lead to the same opportunities when proof is trusted.

Inspiration

We were inspired by a personal and uncomfortable realization: many systems that decide a person’s future are built around where someone comes from, not what they have actually done.

As teenagers, most people are never taught how real work happens or how money actually works. Some grow up with access and exposure, others grow up without it—but in both cases, effort and responsibility are rarely recorded in a way institutions can trust.

For capable young people without early access, opportunity becomes invisible—not because of a lack of talent, but because there is no accepted way to create proof. We wanted to explore a different approach: what if real work, real effort, and real responsibility could become the foundation of trust?

That question led to FinSearch.

What it does

FinSearch is a platform that helps underage teens and young adults build a verified professional and financial identity through real work.

Users are matched to real, skill-based opportunities, assisted by AI in writing professional proposals, and guided through completing tasks and earning income. Each verified action contributes to a long-term score that reflects reliability, growth, communication, and financial behavior.

Instead of replacing existing systems, FinSearch creates a new trust layer that institutions—such as employers, banks, and universities—can understand and build on using real-world data.

How we built it

This project was built as a full front-end prototype to demonstrate the complete user journey from first task to first trusted signal.

Frontend: HTML, CSS, and vanilla JavaScript for a clean, business-grade user experience
State handling: Local storage to simulate identity, scores, and progression
AI integration: A local LLM using Ollama, connected through a lightweight Node.js server, to generate professional job proposals in real time
Architecture: Modular pages representing onboarding, opportunity matching, job completion, score reveal, dashboards, and comparison views

The focus was not on feature quantity, but on clearly demonstrating the core loop end-to-end.

Challenges we faced

One of the biggest challenges was designing a system that felt serious and credible, not gamified or exaggerated.

We also had to balance emotional impact with a professional tone, especially when addressing topics like youth access, trust, and long-term financial identity. Integrating AI in a way that was real and demonstrable—without adding unnecessary complexity—was another key challenge.

Finally, we spent significant time refining the narrative so that the product, demo, and pitch all communicated the same underlying idea.

What we learned

We learned that many large-scale problems in finance and education are not caused by a lack of talent, but by a lack of visibility.

We also learned that good technology alone is not enough—how you frame a problem, how responsibly you design systems, and how clearly you explain them matters just as much as the code itself.

Most importantly, we learned that even a focused demo can communicate a much larger vision when the core idea is clear and grounded in reality.

What’s next

This demo represents only the first step.

In the future, FinSearch could expand into:

Deeper skill mapping and progression tracking across multiple domains
FinSearch for employers to discover proven, reliable talent
Direct integrations with banks, universities, and internship programs
Stronger identity verification and age-appropriate safety mechanisms
A long-term, portable trust score that evolves over decades

Our goal is not to predict potential, but to record it—and make opportunity more accessible through proof.

Built With

Submitted to

✰ LIVE AI Ivy Plus 2026
- Winner [GLOBAL] Demo Honorable Mention
- Winner [UAi] Best Demo

Created by

FinSearch started from a personal experience and a question I couldn’t ignore: why does effort matter so little compared to background?
I led the project from that initial thought all the way to a working demo.

I was responsible for shaping the core idea, vision, and product direction, deciding what problem we were truly solving and how to communicate it clearly. I designed the entire user journey — from signing up, getting a first opportunity, completing work, earning money, receiving guidance, and finally building a long-term score that institutions can trust.

I built the full frontend prototype using HTML, CSS, and JavaScript, focusing on a clean, professional interface that feels serious and trustworthy rather than gamified. I implemented the demo logic that shows how actions turn into signals — scores, eligibility, comparisons, and outcomes.

I also handled the storytelling and presentation: writing the pitch, structuring the demo flow, preparing screenshots, and crafting the Devpost submission so the idea, demo, and narrative all aligned into one clear story.

vidhayank Rolaniya
I primarily worked on the AI integration, backend development, and presentation strategy for FinSearch.

I helped design how AI would fit naturally into the system, particularly for generating professional job proposals and providing financial guidance after users earned money. To ensure the demo showcased real AI capabilities instead of static responses, I set up and supported the local AI integration using Ollama, connected through a Node.js backend.

I also contributed to designing the scoring and signal logic — transforming completed work, user reviews, and financial decisions into structured, meaningful data that institutions could interpret and evaluate.

In addition to the technical aspects, I led the voiceover and video editing for the demo presentation. I helped shape the storytelling approach to ensure the product vision was communicated clearly, emotionally, and effectively for the judges.

Finally, I supported testing and debugging to make sure the complete demo flow worked smoothly end-to-end, especially during the live presentation.

Rohan Rolaniya

Updates

vidhayank Rolaniya posted an update — Feb 24, 2026 03:35 AM EST

Planned Update (Next 20 Days)

In the next 20 days, we will introduce a Live Opportunity Simulation Layer that shows users—and institutions—how specific actions can change future outcomes. Before applying, users will be able to see how completing a job, improving a skill, or making responsible financial decisions would shift their score and unlock eligibility for loans, internships, or university consideration.

Alongside this, we will begin integrating a transparent verification ledger to record key actions and score updates, strengthening trust and auditability while preserving user privacy.

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vidhayank Rolaniya started this project — Feb 22, 2026 11:19 AM EST

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