TickerMaster

Research Screen
Simulation Screen
Track Screen
Track Message
AI Video Broker
Main Product

Inspiration

One tweet can move a stock overnight, and as beginner retail traders, we often follow advices and FOMO with little to no real research while large institutions have Bloomberg terminals on their hands. Approximately 70% to 90% of retail traders lose money over the long term regardless of market conditions, according to US SEC. TickerMaster is a sandbox of financial AI agents that lets you test strategies, learn trading fundamentals, and understand sentiment-driven moves before you place real world orders.

What it does

TickerMaster has 3 core features:

Research: Input any ticker and get a live, cited brief that combines:
- Market data and technical context
- Perplexity-powered catalyst synthesis
- Social sentiment from X/Reddit
- Prediction-market context (Kalshi/Polymarket)
Simulation: Run a multi-agent trading arena where different AI personas react to:
- Volatility regimes
- Breaking narrative shifts
- Each other’s behavior
- Portfolio/risk constraints.
Tracker: Set watchlists and alerts that continuously monitor your tickers and notify you when key signals hit. You can also video call with our AI avatar that will support you as a broker agent 24/7.

How we built it

Architecture:

Frontend: React + TypeScript (Vite)
Backend: FastAPI + WebSockets
Data/Auth: Supabase
Deployment: Vercel (frontend) + cloud backend service

Sponsor/tool integrations:

Modal Inference : Persona inference workflows
Modal Sandbox: Isolated simulation execution
Perplexity Sonar: Cited research synthesis
OpenAI: Commentary, explanation, and educational post-analysis
Browserbase/ Stagehand (integration path) : Automated web data workflows
HeyGen: Conversational broker-avatar UX

Engineering highlights:

Source-aware research pipeline with fallback behavior
Real-time event streaming over WebSockets
Agent orchestration for simulation + tracker systems
Caching/rate-limit controls and production guardrails

Challenges we ran into

One teammate dropped/had to leave :(
Managing API limits especially with hosting/deployment. Hence, ⚠️ disclaimer: Our deployed Vercel website might have hit the token limit by the time you check it out. Come stop by our booth, where we will demo TickerMaster live!

Accomplishments that we're proud of

Built an end-to-end “retail Bloomberg sandbox” in hackathon time
Shipped a working multi-agent simulation system
Delivered citation-backed research summaries from multiple signal types
Implemented persistent tracker workflows with alert context
Created a product that teaches process, not just predictions

What we learned

Running inference and sandboxes on Modal.

What's next for TickerMaster

Live Brokerage Calls: Users can execute real trades with a nostalgic NYSE floor-style voice flow, where an AI broker calls out the order, confirms risk checks, and submits it in real time.

Better portfolio-level risk analytics and scenario testing
Deeper explainability for “why this signal matters now”
Smarter agent memory and adaptive strategy tuning
Reliability upgrades for always-on production performance

DISCLAIMERS: TickerMaster is educational and not investment advice.

This application is resource-intensive and performs frequent reads/writes and large data pulls across multiple services. Our backend is currently deployed on a free-tier plan, so you may experience slow load times, rate limits, temporary downtime, or delayed updates—especially during peak traffic. If the site is bottlenecked when you try it, please stop by our booth for a live demo of TickerMaster!