🧙‍♂️Ÿ Oracle

Building advanced & informed AI-powered Market Data Oracle.

The path towards building the most advanced and informed AI-powered Market Data Oracle unfolds in several phases, with a particular focus on our core model, The Oracle.

The Oracle comprises multiple, tightly integrated components that collaborate to deliver optimal precision. Its structure facilitates constant evolution and enhancement. Ÿ Oracle employs two model types to transform data into predictions:

  • Observers: analyze, refine, and store diverse data sources.

  • Predictors: leverage this processed data to forecast future outcomes.

Ÿ Oracle: Observers

The Oracle employs Observers to relentlessly monitor diverse information sources 24/7: news, market prices, liquidity, on-chain and off-chain activity, and upcoming market events. This rich, self-updating historical database combined with real-time self-browsing capabilities ensures our models remain aligned with rapidly evolving markets.

Ÿ Oracle: Predictors

Upon receiving observed events, our proprietary models analyze, label, and score incoming data. Predictors seek current and past patterns, identify repetitions, draw historical parallels, and factor in context and sentiment. This analysis is then delivered to the appropriate output channels.

Ÿ Oracle: Database

The Oracle's predictive performance and power hinges on its rich, ever-expanding database. This repository encompasses news, social sentiment, CEX market data, on-chain data, ETF data – essentially, every conceivable source of crypto-relevant information. As well as real-time updates ensuring the database constantly reflects the market's pulse

Ÿ Oracle: Accuracy

The Oracle's strength lies in its relentless self-improvement. By incorporating a feedback loop that compares predicted outcomes to market realities, the Oracle will constantly refine its models. This ensures it adapts to shifting trends and delivers ever-increasing accuracy to its users

Ÿ Oracle: Output Channels

The Oracle is designed for seamless integration across multiple output channels. Starting with a real-time updates and reports via Ÿ Telegram bot and channel, future development plans include browser dashboards for in-depth analysis, developer-centric APIs and WebSockets. This flexibility empowers users to interact with the Oracle in the way that best suits their needs

To power our proprietary models, we'll leverage GPU facilities for rapid training and refinement. This infrastructure provides the foundation for scaling our services and introducing exciting new capabilities like decentralized predictors, custom models, and AI-optimized data feeds.

Last updated