Stocrates | Devpost

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Inspiration

63% of Americans live paycheck-to-paycheck, yet financial literacy is rarely taught in schools. When beginners open trading apps like Robinhood, they risk real money in a system they don't understand. We asked: How do people learn markets without fear, pressure, or financial loss?

Technical Inspiration: We saw what was possible with modern AI (e.g., StockBot's real-time market analysis powered by Llama 3.3-70B, and TradingView widgets) and realized the same tech could serve education, not just trading.

Educational Philosophy: Inspired by Socrates, history's greatest teacher, we realized the answer wasn't more predictions but rather better questions. Stocrates takes the technical power of AI + live market data and redirects it entirely toward teaching critical thinking, not making trading decisions.

The Key Difference:

StockBot & similar apps: "Here's a live stock chart and analysis" (useful for traders)
Stocrates: "Why did this happen? What patterns do you see? What would you do?" (teaches investors to think)

We combined Socratic questioning with real historical market data to teach users how to analyze markets, not speculate on them.

What We Built

Stocrates is an AI-powered financial literacy platform that teaches market behaviour through:

Event Analysis - Asks questions like "Why did Tesla drop?" and shows real news, community sentiment, and historical market reactions
Pattern Recognition - Teaches 5 major chart patterns (Breakout, Fakeout, Retest, Head & Shoulders, Continuation) with historical success rates (55-72%)
Paper Trading - Time-travel to the past and practice with fake money using real historical prices
Socratic AI - Instead of predictions, the AI teaches

How we built it

We built Stocrates using a modern web stack focused on speed, transparency, and education.

AI: Groq’s Llama 3.3-70B (pre-trained, open-source)
- Used only for inference (no custom training)
- Guided by strict educational prompts using the Socratic method
- Prevents predictions and financial advice by design
Data Architecture:
Integrated 5 data sources with a 7-layer fallback system for 99.9% uptime
Finnhub → NewsAPI → Reddit → Cache ensures service continues even when APIs rate-limit
Polygon.io provides intraday candles for precise pattern detection
Pattern Analysis:
- Deterministic, rule-based engine (not machine learning)
- Compares historical price movements around similar events
- Shows historical success rates as context, not forecasts

Challenges we ran into

API rate limits & reliability
Financial data APIs are heavily rate-limited
Balancing clarity with complexity
Markets are complex, but the experience needs to remain approachable for beginners.
Ethical boundaries
We intentionally avoided features common in trading apps to keep the focus on learning, not speculation.
Technical Issues and Learning Curve For part of the team, the frameworks and toolings were new, so understanding how everything connected was a challenge, especially under a hackathon timeline.

Accomplishments that we're proud of

Successfully combined ancient teaching methods with modern AI
Created a risk-free paper trading experience using real historical prices
Designed a system that is transparent and honest about its limitations
Built a fully working educational platform in under 48 hours

What we learned

How important accessible financial education really is
Deeper understanding of how markets react to events
AI is most powerful as a teacher and guide, not an oracle
Ethical design in fintech requires clear, enforced boundaries
Hands-on experience with APIs, modern frameworks, and system architecture
The importance of researching what is ethical (and what should be avoided) in financial technology

What's next for Stocrates

More historical scenarios and global market events
Classroom tools and educator dashboards
Personalized learning paths based on user curiosity (e.g., halal stocks)
Accessibility support: Different languages, text-to-speech, etc.

“Learn markets through patterns, not predictions.”

Built With

css
finnhub-api
finnhubapi
groq-api-(llama-3.3-70b)
json
newsapi
next.js
polygonapi
react
reddit-data
stock-market-data
tailwind-css
typescript

Submitted to

WinHacks 2026
- Winner Category: Financial Literacy

Created by

I worked across the full stack, contributing to frontend, backend, API integration, and debugging issues that spanned multiple layers of the system. I helped unblock teammates, resolve setup and merge issues, and ensure features worked cohesively. I genuinely fell in love with the Stocrates idea, building an ethical, educational platform that anyone can use to learn markets made this project especially meaningful and exciting to work on.

Hadiyah Arif
As someone who was intimidated by stocks because of the risk of real money, I was hesitant to explore them. Working on this app not only improved my skills with different frameworks, but also expanded my understanding of the stock market in a way that didn’t require risking any actual money.

suragaafar
I handled event data review and evaluation to measure success and identify gaps. I helped coordinate tasks and maintained clear communication across the team. I documented processes and outcomes for future reference. This improved organization and decision-making for upcoming events

Saidjon Nozimboev
As one of the full-stack developers on Stocrates, I helped to architect the core AI-powered educational features that transform financial literacy learning. My most technically challenging contribution was building a real-time parsing system that extracts confidence levels from unstructured AI streaming responses (Reddit). I also developed the interactive terminology legend sidebar with hover tooltips and integrated three news APIs (NewsAPI, Finnhub, Reddit) with automatic fallback logic for 99.9% uptime. Furthermore I engineered the Socratic method AI prompts that guide users through critical thinking rather than just providing answers. This was more than just a passion project. This was the start of a pivotal moment in my life where the daunting topic of financial literacy was simplified and taught not just in an innovative manner, but with a philosophical approach.

Makhsuma Khamzaliyeva