Quant GorillaAI trading agent for crypto markets
Quant Gorilla scans venues, scores setups, and runs the trade lifecycle—from entry through risk-aware exits—with operator visibility on critical paths. Today: internal validation and paper-style testing; broader access follows when monitoring and controls clear the bar.
No promised ship dates or guaranteed returns. Figures shown in demos or previews may be paper, simulation, or internal test unless explicitly labeled live.
What we're building
- Market scan → decision support
Watches connected venues and context (liquidity, fees, spreads) before size is considered—not a black-box “signal only” story.
- Execution where integrated
Centralized rails first (e.g. Bitunix validation path), with expansion gated on reconciliation and risk policy—not feature flags alone.
- Lifecycle, not entries only
Designed for adds, trims, stops, and exits with automation bounded by hard limits and clear operator surfaces.
Engineering notes
FastAPI backend, structured services, and audit-friendly decision trails where applicable
Telegram / operator-facing status on key paths
Risk and automation policies enforced before scale—not after