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Crypto Signal Board

License: MIT Next.js OpenGradient Deploy

AI-powered crypto trading signals, verified in a Trusted Execution Environment.

Real-time technical analysis for 25 trading pairs, combined with an LLM macro-risk verdict that runs inside an OpenGradient TEE — every prediction is cryptographically signed and tamper-proof.

Live Demo


How It Works

Step What happens Powered by
1 Fetch 48h of 1-hour OHLC candles Binance API
2 Compute 6 technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands, Volume) Local TA engine
3 Run an LLM inside a TEE to assess macro risks (FOMC, CPI, ETF decisions, regulatory news) OpenGradient TEE via x402
4 Produce a combined Buy / Sell / Neutral verdict with confidence score TEE-verified AI
5 Predict 1-hour volatility using an ONNX neural network OpenGradient Model Hub
6 Display everything in a real-time dashboard Next.js 16

Every AI prediction comes with a cryptographic proof — it cannot be altered after the fact.


Why TEE Matters

Traditional signal providers can edit predictions retroactively. With TEE:

  • The AI model runs inside a secure enclave — even the server operator cannot see or modify the computation
  • Every output is signed and immutable — the result is tied to a verifiable on-chain transaction
  • Users get a trust guarantee: what the AI predicted is exactly what you see

Tech Stack

Layer Technology
Frontend Next.js 16, React 19, TypeScript, Tailwind CSS 4
Market Data Binance API (25 pairs, 1h + 30m candles)
AI Inference OpenGradient TEE (LLM via x402 protocol, Base Sepolia)
ML Predictions ONNX model via onnxruntime-node (local inference)
Blockchain viem (x402 payment flow for TEE access)
Deployment Vercel (Stockholm region)

Features

  • 6 Technical Indicators — SMA, EMA, RSI, MACD, Bollinger Bands, Volume analysis with bull/bear/neutral consensus
  • TEE-Verified AI Verdict — Buy/Sell/Neutral with confidence %, backed by on-chain proof
  • Macro Risk Assessment — AI evaluates upcoming economic events and their crypto market impact
  • ML Volatility Forecast — ONNX neural network predicts 1-hour price movement magnitude
  • Interactive Price Chart — 48h candlestick chart with real-time data
  • 25 Trading Pairs — BTC, ETH, BNB, SOL, XRP, DOGE, ADA, and 18 more
  • Auto-Refresh — continuous monitoring with configurable refresh interval
  • Signal History — locally stored past signals for comparison
  • Mobile Responsive — optimized layout for all screen sizes

Architecture

                        Binance API
                            |
                   OHLC candles (1h + 30m)
                            |
              +-------------+-------------+
              |             |             |
        Local TA Engine  OpenGradient   ONNX Model
        (6 indicators)   TEE (LLM)    (volatility)
              |             |             |
              +-------------+-------------+
                            |
                    Next.js API Route
                     (parallel fetch)
                            |
                    Dashboard UI
           (charts, verdicts, indicators)

Model Hub

The volatility model runs locally via onnxruntime-node:

Field Value
Model og-1hr-volatility-ethusdt v0.06
Input 10 x 30-min OHLC candles — tensor float32 [10, 4]
Output Predicted 1-hour volatility % — tensor float32 [1]
Size 7 KB
Source OpenGradient Model Hub

Getting Started

# Clone
git clone https://github.com/cryptoyasenka/crypto-signal-board.git
cd crypto-signal-board

# Install dependencies
npm install

# Configure environment
cat > .env.local << 'EOF'
APP_WALLET_PRIVATE_KEY=0x...your_base_sepolia_private_key...
NODE_TLS_REJECT_UNAUTHORIZED=0
EOF

# Run development server
npm run dev

Open http://localhost:3000.

Environment Variables

Variable Required Description
APP_WALLET_PRIVATE_KEY Yes Base Sepolia wallet private key for x402 TEE payments
NODE_TLS_REJECT_UNAUTHORIZED No Set to 0 for TEE devnet self-signed certs

Note: You need OPG tokens on Base Sepolia to pay for TEE inference. The wallet key is used to sign x402 payment transactions.


Deployment

Deployed on Vercel with automatic deploys from main:

npx vercel --prod

The ONNX model file (7 KB) is included in the repo, so Vercel bundles it automatically.


Built with OpenGradient for the OpenGradient hackathon.

About

AI-powered crypto trading signals verified in OpenGradient TEE. 6 technical indicators + LLM macro-risk verdict + ONNX volatility forecast. Next.js 16 · React 19 · TypeScript · Tailwind CSS 4 · Binance API · onnxruntime

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