Stratos Perception, LLC
The Cerebellum of Physical AI
Physical AI has traditionally approximated the perceptual and reasoning capabilities of the cerebral cortex, leaving a critical sensory gap, relative to the human brain architecture, that makes safety precarious for operations beyond controlled environments.
Stratos Perception's patented ACI™ (Artificial Cerebellar Intelligence) approximates the cerebellum to close the sensory gap, adding to Physical AI systems the autonomic comprehensive estimation layer that they have been missing for interpreting the continuously changing stochastic real world.
AI Innovators Since 1997
Stratos Perception develops artificial intelligence solutions, including novel foundational models, algorithms, and reasoning models, to solve problems concerning automation at scale interacting in the physical world. While Stratos was founded in 2018, our artificial intelligence roots goes back to 1997 with a dissertation on neural networks applied to rocket engines to detect early stages of failures....
ACI™ / Adaptive Control, Reimagined
​ACI™ provides physical AI systems the ability to identify hundreds of hidden time-varying physical parameters in real time, from minimal sensor data, in the systems and environments they operate in.
No other estimation methodology achieves this at the scale and scope that complex autonomous systems require. The implications span plasma control in fusion reactors, autonomous spacecraft navigation, high-speed mobile robotics, and complex industrial systems.
Enabling Level 3+ Digital Twins for Complex Systems
ACI™ enables real-time Level 3+ digital twins for complex systems, something that has remained beyond reach despite decades of effort at national laboratories and universities.
By estimating 100+ hidden physical parameters from minimal sensors, ACI™ provides direct insight into actual system behaviors, degradations, and disturbances as they occur, enabling high-utility bidirectional communications between the twin and the real system.
Training entirely on synthetic data eliminates the need for expensive testbeds or failure histories.
Vehical and Robot Intelligence
Safe autonomous operation in populated, unpredictable environments remains one of the hardest unsolved problems in physical AI. Stratos Perception is addressing it through two complementary and proprietary technologies that together form a comprehensive framework for safe, expert autonomous operation in the stochastic real world.
ACI™ provides real-time physical parameter identification — enabling autonomous systems to understand their actual operating conditions rather than memorized approximations of them.
The Deep Context Network, introduced by Stratos Perception in 2020, abstracts vehicle perception into layered context states that map to safe, nuanced driving actions, eliminating the brittleness inherent in perception-direct control approaches.
Intelligent Two-Phase Flow Thermal Management for Space
AI data centers are driving explosive demand for two-phase cooling systems, on Earth and increasingly in space. Metering and controlling two-phase flows accurately, particularly in microgravity, remains one of the core unsolved challenges in this domain.
Stratos Perception's NASA-funded patented technology applies machine vision and physics-based AI, including convolutional neural networks, to resolve two-phase flow properties that conventional electronic and magnetic sensors cannot. Validated on microgravity flow data, it is acceleration-field agnostic, equally accurate in orbit, in mobile systems, and in terrestrial data centers.
As AI data centers begin moving to space, where microgravity two-phase flow metering is a core unsolved challenge, HFIT is uniquely positioned to address the thermal management demands of next-generation space infrastructure..
