Next-Gen Prediction Market Engine

Pro level Prediction Market Intelligence for everyday traders

Prediction Market Intelligence
For everyday traders

Prediction Market
Intelligence For
Everyday Traders

AI Predictions

AI Powered Predictions

AI Powered Predictions

From ingesting live market data to generating high‑confidence signals at scale.

Event Feeds

On-Chain Tracking

Market Prices & Volume

Live Order Books

Real-Time Data

Instantly streams live order books and social sentiment from global markets, detecting micro-shifts in volatility.

Event Feeds

On-Chain Tracking

Market Prices & Volume

Live Order Books

Real-Time Data

Instantly streams live order books and social sentiment from global markets, detecting micro-shifts in volatility.

Event Feeds

On-Chain Tracking

Market Prices & Volume

Live Order Books

Real-Time Data

Instantly streams live order books and social sentiment from global markets, detecting micro-shifts in volatility.

The Neural Ensemble

Synthesizes six distinct neural networks, from momentum scoring to anomaly detection, into one single signal.

The Neural Ensemble

Synthesizes six distinct neural networks, from momentum scoring to anomaly detection, into one single signal.

The Neural Ensemble

Synthesizes six distinct neural networks, from momentum scoring to anomaly detection, into one single signal.

Scanning markets…

Scan or Analyze

Order Books

Market Prices

On Chain Flow

Outcome Calibrator

Converts model outputs into win probabilities and recalibrates.

Scanning markets…

Scan or Analyze

Order Books

Market Prices

On Chain Flow

Outcome Calibrator

Converts model outputs into win probabilities and recalibrates.

Scanning markets…

Scan or Analyze

Order Books

Market Prices

On Chain Flow

Outcome Calibrator

Converts model outputs into win probabilities and recalibrates.

Code

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class SelfEvolvingAI:
def __init__(self, confidence_threshold): self.confidence_threshold = confidence_threshold self.current_mode = "idle" self.policy_weight = 0.50 # starts neutral def reinforce(self, outcome_reward): # simple reinforcement: reward pushes weight up; loss pushes it down learning_rate = 0.08 self.policy_weight = max(0.0, min(1.0, self.policy_weight + learning_rate * outcome_reward)) # self-evolve: adapt threshold based on performance self.confidence_threshold = max( 0.05, min(0.95, self.confidence_threshold - (0.02 * outcome_reward)) ) def evaluate_trade(self, model_confidence): if model_confidence >= self.confidence_threshold: self.current_mode = "engaged" return "Trade approved; policy activated." return "Trade skipped; waiting for higher confidence." def get_current_mode(self): return f"Current operational mode: {self.current_mode}"
Example usage
ai = SelfEvolvingAI(confidence_threshold=0.60)
conf = 0.67
print(ai.evaluate_trade(conf))
reward: +1 win, -1 loss
ai.reinforce(outcome_reward=random.choice([1, -1]))
print("policy_weight:", round(ai.policy_weight, 3))
print("confidence_threshold:", round(ai.confidence_threshold, 3))
print(ai.get_current_mode())

Reinforcement Learning

Prekog is an adaptive agent. It treats every resolved market as a lesson.

Code

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class SelfEvolvingAI:
def __init__(self, confidence_threshold): self.confidence_threshold = confidence_threshold self.current_mode = "idle" self.policy_weight = 0.50 # starts neutral def reinforce(self, outcome_reward): # simple reinforcement: reward pushes weight up; loss pushes it down learning_rate = 0.08 self.policy_weight = max(0.0, min(1.0, self.policy_weight + learning_rate * outcome_reward)) # self-evolve: adapt threshold based on performance self.confidence_threshold = max( 0.05, min(0.95, self.confidence_threshold - (0.02 * outcome_reward)) ) def evaluate_trade(self, model_confidence): if model_confidence >= self.confidence_threshold: self.current_mode = "engaged" return "Trade approved; policy activated." return "Trade skipped; waiting for higher confidence." def get_current_mode(self): return f"Current operational mode: {self.current_mode}"
Example usage
ai = SelfEvolvingAI(confidence_threshold=0.60)
conf = 0.67
print(ai.evaluate_trade(conf))
reward: +1 win, -1 loss
ai.reinforce(outcome_reward=random.choice([1, -1]))
print("policy_weight:", round(ai.policy_weight, 3))
print("confidence_threshold:", round(ai.confidence_threshold, 3))
print(ai.get_current_mode())

Reinforcement Learning

Prekog is an adaptive agent. It treats every resolved market as a lesson.

Code

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2

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5

class SelfEvolvingAI:
def __init__(self, confidence_threshold): self.confidence_threshold = confidence_threshold self.current_mode = "idle" self.policy_weight = 0.50 # starts neutral def reinforce(self, outcome_reward): # simple reinforcement: reward pushes weight up; loss pushes it down learning_rate = 0.08 self.policy_weight = max(0.0, min(1.0, self.policy_weight + learning_rate * outcome_reward)) # self-evolve: adapt threshold based on performance self.confidence_threshold = max( 0.05, min(0.95, self.confidence_threshold - (0.02 * outcome_reward)) ) def evaluate_trade(self, model_confidence): if model_confidence >= self.confidence_threshold: self.current_mode = "engaged" return "Trade approved; policy activated." return "Trade skipped; waiting for higher confidence." def get_current_mode(self): return f"Current operational mode: {self.current_mode}"
Example usage
ai = SelfEvolvingAI(confidence_threshold=0.60)
conf = 0.67
print(ai.evaluate_trade(conf))
reward: +1 win, -1 loss
ai.reinforce(outcome_reward=random.choice([1, -1]))
print("policy_weight:", round(ai.policy_weight, 3))
print("confidence_threshold:", round(ai.confidence_threshold, 3))
print(ai.get_current_mode())

Reinforcement Learning

Prekog is an adaptive agent. It treats every resolved market as a lesson.

Production Infrastructure

We operate a cloud native, auto scaling architecture.

Production Infrastructure

We operate a cloud native, auto scaling architecture.

Production Infrastructure

We operate a cloud native, auto scaling architecture.

PREDICTION MARKETS

Markets We Predict

Turning sports, politics, and crypto into winning predictions.

Sports Markets

Real-time win probabilities and live odds analysis for NFL, NBA, and UFC.

Sports Markets

Real-time win probabilities and live odds analysis for NFL, NBA, and UFC.

Sports Markets

Real-time win probabilities and live odds analysis for NFL, NBA, and UFC.

Politics & Elections

Forecasting election outcomes and policy shifts.

Politics & Elections

Forecasting election outcomes and policy shifts.

Politics & Elections

Forecasting election outcomes and policy shifts.

Crypto Markets

On-chain signals and sentiment tracking for BTC, ETH, and more.

Crypto Markets

On-chain signals and sentiment tracking for BTC, ETH, and more.

Crypto Markets

On-chain signals and sentiment tracking for BTC, ETH, and more.

Financial Markets

Multi-factor analysis for indices, commodities, forex, and global rates.

Financial Markets

Multi-factor analysis for indices, commodities, forex, and global rates.

Financial Markets

Multi-factor analysis for indices, commodities, forex, and global rates.

Global Events

Analyze geopolitical risks, conflict zones, and treaty outcomes.

Global Events

Analyze geopolitical risks, conflict zones, and treaty outcomes.

Global Events

Analyze geopolitical risks, conflict zones, and treaty outcomes.

Culture & Trends

Quantifying viral moments, box office hits, and award show probabilities.

Culture & Trends

Quantifying viral moments, box office hits, and award show probabilities.

Culture & Trends

Quantifying viral moments, box office hits, and award show probabilities.

PROCESS

Our Compounding System

Our Compounding System

Compound consecutive AI wins to turn 10 trades into 1000x your capital.

STEP 1

STEP 2

STEP 3

01

Pick how much to risk

Decide how much capital you want to put into a single run, like 100 or 1,000 USDC. That fixed amount is the only capital at risk for that entire sequence.

STEP 1

STEP 2

STEP 3

01

Pick how much to risk

Decide how much capital you want to put into a single run, like 100 or 1,000 USDC. That fixed amount is the only capital at risk for that entire sequence.

STEP 1

STEP 2

STEP 3

01

Pick how much to risk

Decide how much capital you want to put into a single run, like 100 or 1,000 USDC. That fixed amount is the only capital at risk for that entire sequence.

GET ACCESS

Token Gated Access

Token Gated Access

Hold $PREKOG to verify your tier and unlock your predictions instantly.

Hold $PREKOG to verify your tier and unlock your predictions instantly.

Basic Access

5M

$PREKOG Staked

$100k Compounding Goal

Pro Grade AI Signals

Community Group Chat

Performance Record

Real time alert, you place your own trades.

VIP Access

10M

$PREKOG Staked

$1M Ladder Done For You

Fund The Ladder

Your share is proportional to your contribution

Vote to continue or exit after each 2×

Claim 100% profits automatically

Basic Access

5M

$PREKOG Staked

$100k Compounding Goal

Pro Grade AI Signals

Community Group Chat

Performance Record

Real time alert, you place your own trades.

VIP Access

10M

$PREKOG Staked

$1M Ladder Done For You

Fund The Ladder

Your share is proportional to your contribution

Vote to continue or exit after each 2×

Claim 100% profits automatically

WHY PREKOG?

Why Choose Us

Why Choose Us

See how we compare against others!

See how we compare against others!

PREKOG

First prediction market AI that routes value back to holders

Scans Polymarket and beyond 24/7; not tied to one venue

Real time order book intelligence

Hands off mode, not just alerts

Multi market coverage

Others

Signal channels only; no execution

Single market focus

No holder value loop; subscribers pay

No real AI

No integrated compounding system

MEET THE TEAM

Get to Know Us

Get to Know Us

Everything you need to know about your founding team.

Lee

Leads product and strategy; focused on turning prediction market data into intelligence.

user pic

Lee

Leads product and strategy; focused on turning prediction market data into intelligence.

user pic

Lee

Leads product and strategy; focused on turning prediction market data into intelligence.

user pic

Luka

Owns the models and infrastructure; builds the real time alert engine and execution stack.

user pic

Luka

Owns the models and infrastructure; builds the real time alert engine and execution stack.

user pic

Luka

Owns the models and infrastructure; builds the real time alert engine and execution stack.

user pic

Jess

Drives growth and brand; runs community, partnerships, and go to market.

user pic

Jess

Drives growth and brand; runs community, partnerships, and go to market.

user pic

Jess

Drives growth and brand; runs community, partnerships, and go to market.

user pic

KYC verified by

KYC verified by

Roadmap

2026 Roadmap

Live Now

AI predictions live

Real-time neural network predictions.

Revenue share active

Exactly proportional to your contribution.

Buyback engine

Wins automatically buyback & burn.

Telegram access

Exclusive VIP chat for VIP members.

Token launching

Wed Jan 28 @ 2PM UTC

Phase 1 · Q2 2026

Fully automated bots

Hands free trading executed through a TG bot.

Affiliate network

Rewarding community growth with referrals

Mobile apps

iOS and Android applications for paid access.

DAO launch

Decentralized decision making.

Partnership network

Strategic alliances with major prediction markets.

Phase 2 · Q3–Q4 2026

AI chat assistant

Conversational interface for deep data queries.

Cross‑platform

Seamless across web, mobile, & desktop platforms.

Referral 2.0

Enhanced reward structure for affiliates.

Global expansion

Support and markets for international regions.

CEX listings

Expanding reach to centralized exchanges.

Get in touch

Ready to Trade Smarter? Let’s run the Ladder

Get AI signals or go fully hands off.

support@prekogai.com

Get in touch

Ready to Trade Smarter? Let’s run the Ladder

Get AI signals or go fully hands off.

support@prekogai.com

Get in touch

Ready to Trade Smarter? Let’s run the Ladder

Get AI signals or go fully hands off.

support@prekogai.com

Roadmap

2026 Roadmap

Live Now

AI predictions live

Real-time neural network forecasts for all major sports.

Revenue share active

Stakers earn direct yield from platform fees weekly.

Buyback engine

Protocol automatically repurchases tokens from open market.

Telegram access

Exclusive VIP channels for verified token holders.

Uniswap liquidity

Deep liquidity pools for seamless trading.

Phase 1 · Q1 2026

Major CEX listings

Expanding reach to tier-1 centralized exchanges.

Affiliate network

Rewarding community growth with robust referral systems.

Mobile apps

Native iOS and Android applications for on-the-go access.

DAO launch

Decentralized governance for community-led decision making.

Partnership network

Strategic alliances with major sports data providers.

Phase 2 · Q2–Q4 2026

Fully automated bots

Hands-free trading execution based on AI signals.

AI chat assistant

Conversational interface for deep data queries.

Cross‑platform

Seamless experience across web, mobile, and desktop.

Referral 2.0

Enhanced multi-tier reward structure for power users.

Global expansion

Localized support and markets for international regions.