Attesio Publishes Quantitative analysis of Publicly trader crypto pairs, Confluence scoring, multiframe agreement, market regime classification, and a published records of every outcome the system produces. This system is developed by SynthesysLab's engineer. The team is used latest tools and technologies Means (TimeScaleDb, Postgres, Redis, Typescript langauge (For real time Processing), Machine Learning Model CNN-LSTM.
We built Atessio because crypto traders face an overwhelming amount of market data, indicators and conflicting signals, making it difficult to turn information into a structured trading decision.
We wanted to build something different: not another platform that simply throws more indicators at traders, but an AI-powered system that brings multiple market factors together and validates them through a structured process.
Our approach evolved from experimenting with individual indicators to building a multi-factor confluence and 9-stage validation pipeline, including multi-timeframe confirmation and structured risk-management levels.
Today, Atessio generates LONG, SHORT and NO-TRADE market outlooks with entry, stop-loss and take-profit levels. Our next goal is to evolve it into a broader AI-powered market-intelligence and trading infrastructure layer for Web3.
We’re launching on Product Hunt to get feedback from traders, AI builders and Web3 professionals and learn what we should build next.