Green Vectors for autonomous systems
Make more useful information fit where the system actually has to run.
If memory, power, bandwidth, thermal limits, or cloud dependence are constraining what your AI system can keep and use locally, tell us about the platform and workload. Morphos will determine whether a focused Green Vectors evaluation is technically worth pursuing.
Vehicles, drones, robots, satellites, sensors, portable systems, and embedded hardware. We evaluate the architecture against the target workload and hardware rather than extrapolating results from unrelated benchmarks.
Start with the constraint
What keeps the capability off the platform today?
A capable model can still be impractical if the system cannot hold enough useful information, move it quickly enough, stay within the available power and thermal envelope, or remain useful when connectivity degrades.
Morphos evaluates Green Vectors against the system as it actually exists: the target hardware, representative data, current architecture, and the constraint preventing the desired capability.
Morphos has not published non-language performance results. Performance for perception, sensor, telemetry, and decision-support workloads must be established separately on the actual platform, data, and task.
Review
Technical review and confidentiality.
Specific architectures, configurations, and results are shared under appropriate confidentiality agreements and export review. Security and data-handling requirements are defined with the partner before an evaluation begins. Share only what you are cleared to share in a first message.
Platform evaluation
Tell us about the system.
The platform, the workload, and the constraint are enough to determine whether a measurable comparison is worth defining.