Sintinel combines real-time sentiment analysis from news, social media, and SEC filings with quantitative models to surface actionable trading signals. The platform uses a multi-agent AI architecture — where specialized models for sentiment, quant analysis, and risk assessment cross-check each other — to give retail traders the kind of signal intelligence that used to require a quant desk. Every signal is scored, tracked, and held accountable against actual market outcomes.
Avid technologist, basic trader. Sintinel was born from a personal interest in applying AI and quantitative methods to retail trading — combining sentiment analysis, multi-agent LLM scoring, and rigorous signal accountability into a platform that holds itself to the same standards as the trades it recommends.