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Real-world data collection and testing is slow, expensive and difficult to reproduce at scale, which limits the applicability of robots in different environments. Fidelis AI is developing an agnostic AI brain designed to adapt at runtime enabling intelligence to transfer and improve as the body and environment change.
CHANGE THE WORLD.
KEEP LEARNING.
A robot rarely sees one fixed world. Sensors, lighting, dynamics and operating conditions change over time. The adaptive core is designed to recognise those shifts and recover useful performance through continued experience.
The graph on the right shows real time adaptation of our AI core as it goes through five domain shifts. It plays forward in sample-time to show performance changing as a system enters each new domain.
01 · PLUG + PLAY INTELLIGENCE
FidelisAI is building a common adaptive intelligence layer that interfaces with a robot's sensors, actuators and control stack. Instead of developing a separate intelligence system for every platform, the core learns how a new embodiment can perceive, move and act.
02 · SHIFT DETECTION
The system continuously monitors its inputs, dynamics and performance to identify meaningful shifts — from changing environments and sensor conditions to new payloads, dynamics or an entirely different robotic body.
03 · RUNTIME ADAPTATION
When a shift is detected, the adaptive core uses new experience to update how it interprets the world and controls the embodiment. The aim is to recover and improve capability at runtime without rebuilding the autonomy stack from the ground up.
FidelisAI brings together AI, robotics, and engineering expertise around one goal: build intelligence that can adapt across robotic bodies and environments.
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