ADCT is a data-driven trading approach that uses attention metrics to spot high-potential tokens before they go mainstream. In a noisy market, we focus on trading attention — not speculation.
Our scoring engine tracks signals across social, platforms, and on-chain sources to surface the top 1% of tokens with real momentum.
We track attention across multiple channels to score tokens with greater precision than traditional indicators. When signals align, we surface top opportunities in seconds.
Track new token launches on Solana, Base, BNB, and Ethereum in real-time. We instantly index each token and its attention signals across social, platforms, and on-chain activity.
Apply our Machine Learning scoring to unify attention signals, weighted by past performance and outcome correlations.
Tokens above dynamic attention thresholds trigger early entry; 99% of low-signal tokens are filtered out.
Enter trades when attention thresholds hit; profit-taking auto-triggers on attention decay.
ADCT processes massive data streams in real-time on high-speed, scalable infrastructure. We detect attention spikes faster than any manual method.
Real-time data from social APIs, blockchain nodes, and scraped platforms without APIs.
Parallel ETL pipelines turn raw data into standardized attention metrics.
Machine learning models score attention and detect anomalies in real-time.
Automated trades run on attention signals; dashboards track performance live.
We're accepting a limited number of users for early access to ADCT and attention-based trading.