# JARVIS — crypto analytics and live signal stack

Since 2018 we have evolved JARVIS — a cryptocurrency-focused analytics and signal engine that ingests market and narrative data, applies proprietary models (including NLP-heavy workflows), and connects to live trading paths, today including Bitcoin and additional pairs, with workloads spread across multiple AWS regions and a polyglot PHP and Python estate.

## 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

1. **Invested in ingestion and normalization first** so downstream models saw consistent time series and text artifacts instead of ad-hoc CSVs.
2. **Separated research sandboxes from production paths** so new logic could be promoted only after it survived realistic execution constraints.
3. **Used AI-heavy workflows** where they compress analyst time — not as a gimmick — and kept human review on the risk boundaries.
4. **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.

## Proof

Live systems

Production analytics, signal generation, and execution-side integration.

## Public reference

Details of models and positions are intentionally not published.