9Lives Agent
An autonomous system designed for open prediction markets on high-impact assets with hourly and daily resolutions.
Overview
The WowFi app unlocks three interconnected categories that work together to provide comprehensive web3 observation:
Crypto Currencies (Tokens)
Trading-focused insights and analysis for cryptocurrency tokens, providing real-time market intelligence and trend identification.
TradingProjects
Discovery and investment analysis for crypto projects, including whitepaper summaries, timelines, and key announcements.
Discovery & Investment9Lives Agent
CVAS-powered intelligence layer that supercharges decision-making with proprietary reasoning models and real-time prediction capabilities.
CVAS-Powered predictionThe Agent
WowFi 9Lives_Agent is an autonomous system designed for open prediction markets on high-impact assets like BTC, GOLD, MONAD, and NVIDIA (with hourly and daily resolutions).
Unlike traditional prediction systems, the 9Lives Agent operates continuously, learning from each prediction outcome to improve accuracy over time. The system automatically retrains its models using resolved predictions, enabling repeated improvements in accuracy and adaptability.
Architecture
Dual Purposes
Unlike traditional apps, 9Lives Reasoning serves dual purposes:
Proprietary Model
WowFi's in-house 9Lives Reasoning engine, trained on ultra-pure market data for unmatched accuracy. The model leverages CVAS-filtered data sources to ensure predictions are based on verified, noise-free information.
In-App Integration
Real-time tools embedded in the app (Phase 1 build focus), enabling users to query predictions on-the-go. Provides an Agent interface where users input queries and receive probabilistic predictions instantly.
CVAS-Integrated Data Pipeline
Currently building CVAS (Cross-Validation Analysis Stack) model that aggregates data from global sources and applies filtering to deliver 100% pure, verifiable information.
This feeds directly into the 9Lives Reasoning model, enabling next-level analysis that far surpasses generic market agents.
Fundamental Substance
Economic indicators and news sentiment analysis without noise. CVAS filters out bot-generated content, spam, and low-quality sources to ensure predictions are based on genuine market signals and verified information.
Economic indicators from verified sources
News sentiment analysis (noise-filtered)
Bot and spam detection
Technical Analysis
Price patterns, volume trends, and volatility models processed through advanced algorithms. The system analyzes historical patterns and real-time market movements to identify trends and potential price movements.
Price pattern recognition
Volume trend analysis
Volatility modeling
Workflow
The Agent pulls and logs real-time market events according to 9Lives' prediction market setup. This includes:
Real-time price feeds from multiple exchanges
Market event logging (trades, volume spikes, news events)
CVAS-filtered social media signals
Economic indicator updates
Converts records into a scalable vector database for efficient querying. The longer the agent runs, the stronger the reasoning result.
Vector embeddings for semantic search
Time-series data indexing
Historical pattern storage
Continuous learning from resolved predictions
Key Benefit: The system improves accuracy over time as it processes more data and learns from 9lives actual outcome.
Retrieval-Augmented Generation delivers an Agent interface in the WowFi app users input queries, and the Agent outputs probabilistic predictions.
Natural language query processing
Context-aware retrieval from vector database
Probabilistic prediction generation
Real-time response formatting
Continuous Retraining Loop
Regardless of whether prediction outcomes resolve as 'True' or 'False', the Agent automatically retrains the model using these comparisons, enabling repeated improvements in accuracy and adaptability over time.
Key Features
Real-time Market Event Tracking
Continuously monitors and logs market events in real-time, ensuring predictions are based on the most current market conditions.
Scalable Vector Database
Efficient querying through vector embeddings enables fast semantic search and pattern matching across historical data.
Agent Interface [Utility Feature Only]
Natural language queries processed through RAG (Retrieval-Augmented Generation) for intuitive user interaction.
Continuous Model Improvement
Automatically retrains models using resolved prediction outcomes, ensuring accuracy improves over time without manual intervention.