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Tenki AI

Tenki is an AI forecasting platform for prediction markets. Ideal for traders and bettors, it helps identify market edges by providing high-accuracy probabilistic estimates.

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January 8th, 2026

About Tenki AI

Tenki is an AI forecasting platform that helps prediction market traders achieve higher win rates without manual data crunching.

The platform utilizes a specialized multi-agent AI system that encodes game theory and Bayesian updating to process thousands of signals across sports and political markets. Verified across 10,000+ test questions, Tenki maintains a 76% binary accuracy rate. It provides traders with a distinct edge on platforms like Kalshi and Polymarket by delivering daily probabilistic estimates and automated risk management suggestions.

Beyond simple predictions, Tenki integrates professional-grade trading tools directly into its dashboard. Users receive Kelly Criterion bankroll allocation percentages to optimize position sizing and proprietary "Exit Price" alerts that function as automated stop-losses. This combination of predictive accuracy and structural risk control allows both retail bettors and institutional forecasters to navigate volatile event markets with quantifiable confidence.

Browser / Automation – Interactive Trading Dashboard Toolchain – Python-based Multi-Agent Architecture, REST API

Capabilities – Binary event forecasting, Kelly Criterion optimization, Exit signal generation

Discover Tenki and thousands of other AI tools on Beyond The AI - your trusted directory for AI solutions.

Who is using Tenki AI?

Prediction Market TradersSports BettorsPolitical analystsFinancial risk managersQuantitative researchers

Key Features

8 features
  • Multi-Agent AI Forecasting
  • 76% Verified Binary Accuracy
  • Kelly Criterion Integration
  • Proprietary Exit Price Alerts
  • Daily Dashboard Updates
  • CSV Data Exporting
  • Sports and Political Market Coverage
  • Expected Value (EV) Calculations

Use Cases

4 use cases
  • Optimizing trade sizing for Kalshi event contracts
  • Finding arbitrage opportunities in political markets
  • Improving win rates in NBA and NFL sports betting
  • Exporting historical market data for quantitative research
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