What makes the fleet as good as it is: the data it learns from.
Anyone can buy the same robot body and the same navigation software. What they can't buy is what a MoLogica fleet has already seen, been corrected on and learned from. Every shift adds to it.
Every patrol is a dataset
Each patrol is recorded end to end: position, movement, camera images, inspection verdicts and the reasons behind them. A single simulated patrol produced 1,477 frames of evidence. It's kept in a format you can take with you, so nothing is locked in.
Corrections are the most valuable data
When an operator takes over, in plain language or by joystick, the whole episode is kept: what the robot was doing, what the human did instead, and why. The fleet learns from exactly the moments it fell short. Corrected once on one site, learned for every site.
Answers on the robot, in a millisecond
Inspection checks start as judgements and become models that run on the robot itself with no network. In an overnight simulation run the robot drove itself to 538 positions over four hours with no navigation failures and trained a check to 95% accuracy. Those answers come in about a millisecond.
How it's applied
New models reach your fleet only after they prove better than the current one on your own site's twin. Fleet operations controls which model runs on which robot, with instant rollback. Your industry pack is built from your site's own objects, and your history travels with you when the hardware changes.
Mixed fleets make better data
Different bodies, different sites, different nights. Diverse experience trains better models than volume from one robot in one warehouse.
Recording, correction logging and model training are proven in simulation; real-site datasets start with the first pilot.
Ready to see robots patrolling your site?
Before any hardware is bought, we can build a simulated copy of your site and show the fleet patrolling it at night while you configure the checks in plain language.