Bot integrators
Pull published forecasts into execution logic, alerting engines, and rankers without rebuilding the model layer.
SOLUTIONS
Use the same signal intelligence in different product layers.
One model stack. Multiple signal products.
Lunatrix is not limited to a landing page. The same inference layer can serve bots, live user dashboards, analyst workflows, and internal trading operations without forking the intelligence into separate systems.
Primary use cases
Built for teams that need signal delivery, not just a model demo.
Signal publishers
Expose the same calls on a public surface so users can inspect live ideas before building their own integrations.
Research desks
Route the model output into internal market reviews, morning briefings, and post-trade validation loops.
Signal calls can stay simple.
Integrators should not need the frontend to be online before they can consume Lunatrix forecasts.
fetch("http://127.0.0.1:8000/api/current-signals?action=actionable&limit=12")
.then((response) => response.json())
.then((payload) => {
console.log(payload.signals);
});Public signal boards
Mirror the current forecast layer on the site so non-technical users can still benefit from the model.
Operator interfaces
Use the backend as a stable surface for internal tools that need signal freshness without direct Python coupling.
Execution assistants
Combine published signals with downstream risk or routing logic instead of collapsing everything into one service.