Architecture
VolatilityX ingests, processes, and analyzes vast amounts of financial and social data in real time (or near-real time). We then transform these raw data streams into actionable insights—primarily through AI Agents that collaborate to answer user queries or autonomously detect market anomalies (“alpha”). Finally, we broadcast these insights across multiple channels, including social media (Twitter, TikTok, Reddit) and a specialized user terminal (portfolio manager).
Key Architectural Pillars
Data Ingestion Collecting information from diverse, heterogeneous sources, including real-time price feeds, social chatter, financial statements, and so on.
Data Processing Pipeline Cleaning, normalizing, and transforming data into structured formats suitable for advanced analytics and feature extraction.
Analytics & Machine Learning Running anomaly detection, pattern recognition, correlation analysis, and other ML tasks to produce indicators or identify “alpha” signals.
Multi-Agent System Orchestrating specialized “expert” Agents—powered by large language models (LLMs)—that collaborate to handle user queries, perform deeper analysis, and craft final outputs.
Information Dissemination Delivering insights through public channels (socials) and private experiences (our terminal), ensuring immediate availability and interactivity.
This architecture not only provides robust, scalable performance but also accommodates continuous improvement. As we gather more data or refine AI models, each layer can adapt without disrupting the entire pipeline.
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