ReverseML Try Mini
ReverseML Mini

An adaptive AI runtime that lives on the device

ReverseML Mini observes authorized system processes, learns recurring operational patterns, and gradually assists with approved functions — under explicit safety boundaries. It runs locally, adapts to available hardware and self-calibrates to the platform it is deployed on.

View measured proof Download
How it earns trust — one step at a time
Observe→ Learn→ Predict in shadow mode→ Advise→ Assist after confirmation→ Control only approved processes

On drones, satellites and other critical systems the native deterministic controller and an independent safety layer always retain command. Mini is an intelligent apprentice and coordinator — never an uncontrolled replacement for control.

One runtime, many platforms — it self-calibrates to the hardware it is installed on
Desktop Mobile Industrial systems Robotics Drones Satellites Other edge devices
Available now
  • Local model
  • Private memory
  • Document grounding
  • Resource Autopilot (CPU / RAM / battery / thermal)
  • Expert editions
Built & measured in the lab
  • Process mining
  • Shadow prediction
  • Safety gate
  • Audit chain
  • Deterministic replay
  • Synthetic benchmarks
Research roadmap
  • Real gradual process assistance
  • Drone integration
  • Satellite integration
  • Industrial adapters
  • Certified safety-critical use
Process Assimilation — current status
ReverseML Process Assimilation is currently collecting privacy-preserving desktop metadata for real-world shadow-mode evaluation. Synthetic tests have validated the mechanism and safety architecture; real-data performance is now being measured against simple baselines.
This is real-data evaluation, not self-learning — it does not retrain or change the model. Metadata only: app category, battery, CPU — never titles, paths, URLs or content.
Positioning: Mini is an adaptive on-device runtime — deterministic process discovery + system modelling + resource awareness + a compact language interface. It learns authorized workflows in shadow mode; it does not understand or control any system on its own.