Edge AI Deployment, as a Service
We make AI models run on embedded hardware at single-digit watts. Your model works in the cloud; it needs to run on the machine. That gap is where projects stall for months, and it is exactly what we build for our own product.
// Quantization, memory budgets, power envelopes
// Proof running live at try.godel.space
How We Engage
Edge Readiness Assessment
A fixed-fee analysis of your model against your target hardware: quantization path, memory and throughput budget, projected latency and power, the risks that will bite, and a concrete deployment plan. If it will not fit, you learn that in a report instead of a quarter of engineering time.
Deployment Sprint
We take your model to your target: running on-device at your latency and power budget, with a benchmark report, a reproducible build, and deployment scripts. Fixed scope and fixed fee, defined from the assessment findings.
Sprint + Support
The sprint plus sixty days of engineering support as your team takes over. Every engagement starts with the assessment, and we take one engagement at a time: you get the same engineering that built our product.
Who This Is For
Robotics, drone, industrial vision, Earth observation, and defense subsystem teams with a trained model that needs to live on embedded edge hardware, and a team whose time is worth more than the fee.
// Our proof: earth observation foundation models running on
// satellite-class edge hardware, live at try.godel.space