Finance / Case study
PolyHuntr
Real-time analytics for prediction markets: who is trading well, and why
In short
PolyHuntr is live, real-time analytics for Polymarket: streaming market activity, a daily risk-adjusted wallet ranking, back-testing, and on-demand AI analysis.
ResultThousands of markets followed in real time, distilled into a daily ranking and on-demand explanations.
- Status
- Live
- State
- Live
- Data
- Real-time
- Coverage
- Thousands of markets
- Analysis
- On demand
- Built with
- Elixir / Phoenix / TypeScript / PostgreSQL
Inside the project
01 / 01Live capture from polyhuntr.com, November 2026.
The brief
The problem
Prediction markets move around the clock across thousands of markets, and every trade is public. The information is all there, but nobody can watch it all, tell skill from luck in a wallet's history, or keep up as prices change.
What we did
Our approach
We built a real-time analytics platform on Elixir/Phoenix. It streams market and trade activity continuously, scores public wallets on risk-adjusted performance, and publishes a daily ranking. Users can follow wallets, test ideas against history before acting, and ask for a plain-language analysis of any wallet or market.
Features
What it does
- 01
Real-time market and wallet streaming
- 02
Daily wallet ranking
- 03
Wallet following with risk limits
- 04
Back-testing and portfolio simulation
- 05
On-demand AI analysis
- 06
Alerts to chat apps
Results
What happened
- Live at polyhuntr.com
- Market and trade activity streamed in real time
- Daily ranking of public wallets by risk-adjusted performance
- Back-testing against history before any capital is involved
- On-demand AI analysis of any wallet or market
Services
What this work shows we do
Custom software
Service pageSoftware built around how the business works, and run after launch.
AI automation
Service pageModels wired into the tools your team already uses, with logs and limits.
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How we work
How a change reaches production
The same five gates for our own products and for yours. Nothing reaches your customers on the strength of a demo.
- 01 · Isolate
Its own branch and workspace
Every change starts in a separate copy of the code, so work in progress never touches what is live.
git worktree add .worktrees/your-change - 02 · Build
Engineers with AI agents
Agents write and test code beside us. They hold no passwords: every call they make goes through our gateway, which checks it and logs it.
agent → gateway → policy · audit · call - 03 · Prove
Evidence, then review
Tests, before-and-after screenshots of the running app, then independent reviewers. It does not move on until no serious finding is left.
review: 0 high · 0 medium → pass - 04 · Ship
Deployed and checked live
The pipeline builds and deploys. Then we check the running service itself, not just a green build.
replicas 1/1 · image sha matches · health 200 - 05 · Watch
Checked every night
Each integration we run is tested against its provider every night, so a changed API is caught before your team notices.
nightly: each integration vs its provider