Bandwidth is finite.
Continuous video can overwhelm the links connecting distributed sensors to shared compute.
The world is full of sensors. DayStar makes their data work harder.
Machine vision compression and sensor transport built to scale physical AI.
Feature intelligenceTHE CHALLENGE
More cameras. More autonomous systems. More data than networks can carry. Physical AI needs a better way to connect what machines sense with what they understand.
Continuous video can overwhelm the links connecting distributed sensors to shared compute.
Power, memory, and compute constraints shape what an autonomous platform can do.
Machine vision needs the information that supports detection, tracking, and decisions.
THE DAYSTAR APPROACH
DayStar develops task aware sensor transport: extracting and compressing useful features close to the sensor, then connecting them to the compute that completes the picture.
01 / CLOSE TO THE SENSOR
The edge runs the front of the model and produces compact features for the downstream task. This creates a practical way to share the work between a resource constrained device and more capable compute.
FEATURE CODING FOR MACHINES
Our first offering brings MPEG Feature Coding for Machines (FCM) into real time, with implementations demonstrated on visible, thermal, and low-light imagery.
Compared with H.265 at matched detection accuracy.
At the same bitrate in DayStar’s reported evaluations.
Demonstrated on NVIDIA Orin.
Company-reported results. Performance depends on model, imagery, hardware, task, and configuration. Request benchmark methodology.
FROM RESEARCH TO IMPLEMENTATION
A development path from flexible software integration to optimized hardware.
SOFTWARE
Integrate FCM into existing applications across various platforms
MODEL OPTIMIZATION
User interface and engine for optimized deployment, adapting models to specific use case
HARDWARE ROADMAP
A path to hardware acceleration, with IP blocks designed for embedded platforms and future processor integration.
ONE FOUNDATION. MANY POSSIBILITIES.
From a single sensor to a fleet of autonomous systems, efficient machine vision creates room to do more.
AUTONOMOUS MOBILITY
Connect cameras, onboard intelligence, and shared compute across autonomous vehicles and fleets. Compact feature streams can support perception while easing the demands of moving and retaining video.
BEYOND VIDEO
FCM is the starting point. Our roadmap extends task aware transport to more sensors and to a shared view across platforms.
Real-time machine vision compression and an implementation toolchain.
Deliver the most useful information first as available bandwidth changes.
Extend the approach toward radar, RF, acoustic, and other sensor inputs.
Connect information across platforms so systems can build a richer picture together.
THE PEOPLE BEHIND DAYSTAR
DayStar brings together expertise in video compression, AI, standards, intellectual property, and commercial deployment. Our team connects foundational research with the systems that put it to work.
Founder, CEO & President
Experienced founder, engineer, patent lawyer. Founder of OP Solutions. Sold legacy OPS codec portfolio in 2026 for published amount of $37M.
Technology & Strategy
More than 30 years of experience commercializing technology across commercial and defense markets.
Director of Research
Video compression researcher and named inventor on more than 100 U.S. patents.
Senior Researcher
Florida Atlantic University department chair, National Academy of Inventors Fellow, and named inventor on more than 130 U.S. patents.
Defense Liaison & Subject Matter Expert
Experience across Air Force special operations, DIUX, AFWERX, and defense technology programs.
Chief Operating Officer
More than 30 years of commercial and defense experience, including serving as COO of Magic Leap.
A CLOSER LOOK
FCM represents information used by a machine vision model as compressed features. It supports splitting inference between an edge device and downstream compute, with efficiency evaluated against the intended machine task.
DayStar’s implementation approach includes a software SDK and API, an AI toolchain, and a hardware acceleration roadmap. An engagement starts with your sensors, models, hardware, network constraints, and performance requirements.
Applications include autonomous mobility, industrial automation, surveillance, infrastructure monitoring, and defense systems—particularly where cameras and compute are separated by limited network capacity.
Yes. Contact the team to discuss a live demonstration, benchmark methodology, or an evaluation using your own application requirements.
Contact DayStarBUILD WHAT COMES NEXT
Explore a demonstration, a technical evaluation,
or a collaboration with DayStar.