Caliber Engine AI

Caliber Engine plugs into your brokerage account — the vendor states compatibility with 10+ brokers — and takes over the full trading cycle: scanning a categorized watchlist of symbols across tech, financials, energy, healthcare, and consumer sectors, evaluating setups in real time, routing orders, managing open positions with trailing stops and take-profit targets, and writing every outcome to memory to inform future decisions. The loop runs every market day without human input at the execution layer.

The differentiating claim is the memory layer. Rather than static rules that decay as market conditions shift, the engine is described as filing each trade outcome and using that history to sharpen how it reads future setups. The vendor frames this as the engine learning what works over time — though the mechanism is not publicly documented, so teams should treat this as a proprietary black box rather than an auditable ML pipeline.

Calibr Engine fits traders who want to attach an AI decision layer to an existing funded account and step back from manual execution — including paper trading via a connected paper account before going live. It breaks down for anyone who needs to inspect the underlying signal logic, build on top of the engine’s outputs via API, or run the system inside their own infrastructure. No API is available and no self-hosted deployment exists, so every signal, decision, and order routes through Caliber Engine’s hosted environment. Teams that eventually need programmatic access to signals or want to combine this engine’s outputs with a proprietary risk layer will hit a hard stop with no workaround short of switching platforms.

The subscription is paid-only with no free tier; the vendor offers a paper trading path described as risk-free testing before committing to live execution. The engine surfaces a live telemetry view showing active positions, decisions per session, and execution latency — giving operators a real-time status window, though not a configurable dashboard.