Challenge
Crypto markets generate enormous noise. Building something durable meant combining fast market data, language-heavy sentiment features, and disciplined signal generation — then operating it where milliseconds and regional redundancy matter once capital is live.
Approach
Invested in ingestion and normalization first so downstream models saw consistent time series and text artifacts instead of ad-hoc CSVs.
Separated research sandboxes from production paths so new logic could be promoted only after it survived realistic execution constraints.
Used AI-heavy workflows where they compress analyst time — not as a gimmick — and kept human review on the risk boundaries.
Ran services across AWS regions to balance latency, failover, and data residency expectations for always-on trading infrastructure.
“We don't invent numbers. What we publish matches what clients are comfortable having on the record.”
Outcome
JARVIS remains under active development with live trading participation: a reference architecture for how Craft & Logic treats data-heavy, regulated-adjacent systems that never get to pause for maintenance windows.
Proprietary research and execution infrastructure developed in-house.
Proof
Live systems
Production analytics, signal generation, and execution-side integration.
Details of models and positions are intentionally not published.