Building the infrastructure AI systems are missing
AI systems are limited by compute, memory, and data movement.
Most fail at the same boundaries.
We build below them.
NetViper is an infrastructure company focused on performance-critical AI systems.
We operate where:
- GPU constraints define scale
- latency determines viability
- correctness cannot be compromised
This is infrastructure. Not application development.
Most teams optimize models.
Some scale hardware.
Few address the underlying constraints.
- GPU utilization becomes the bottleneck
- inference pipelines degrade under load
- memory handling introduces drift or loss
- data movement limits real-time performance
These problems cannot be solved at the surface.
We work closely with a small number of teams operating at the edge of current AI systems.
Work is focused, technical, and bounded by measurable outcomes.
No templates. No unnecessary abstraction.
- performance-first design
- control over convenience
- correctness under real conditions
We are actively working on new approaches to AI infrastructure at the systems level.
This includes problems around resource efficiency, system memory, and data movement where existing approaches begin to fail at scale.
This work is developed alongside teams operating in production environments.
Engineering
We build below the framework layer.
Kaio — a framework for writing GPU kernels in Rust, compiled to PTX at build time. Designed for full control over memory, execution, and performance.
If you're working on systems where performance is becoming the constraint, we should talk.
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