Tailored Solutions
Mallorn ships tuned for field-health anomalies: nutrient deficiency, weed pressure, drydown. But that's a configuration of the platform, not the platform itself.
What's underneath
The stack is three swappable stages: onboard multi-channel imaging, an edge classification model, and a proportional actuation response, or detection and reporting only if actuation isn't relevant to your use case. None of the three is hard-wired to our default class list.
What can change
Sensor channels
RGB, NIR, or a different multispectral configuration, depending on what the target requires.
Target classes
Whatever your labeled dataset defines.
Response logic
Proportional actuation, threshold alerts, or detect-and-report with a human in the loop.
Deployment
The same edge hardware and inference pipeline, reconfigured rather than rebuilt.
What we need from you
A labeled dataset (or a credible plan to build one) and a clear definition of the target. From there we scope a tailored model and deployment. The underlying engineering is already proven in production.
Get in touch
If you have a specialized detection problem this could fit, tell us about it.
Email hello@mallorn.app →