Robot brains are growing faster than robot bodies. We’re the missing infrastructure.
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CHALLENGE
Three forces are converging to break today’s robot infrastructure.
Transformer-based perception and planning models demand 10–100× the FLOPs of 2022 baselines. On-robot GPUs can’t keep up without thermal, weight, and cost penalties that make retrofits impractical.
A 100-robot warehouse generates petabytes of sensor data monthly. Cloud round-trips add 50–200 ms of unpredictable latency — far too slow for pick-and-place SLOs under 30 ms.
Duplicating high-end GPUs on every robot raises CapEx, heat, and field failure rates. But there is no purpose-built compute layer between the cloud and the robot.
The result: autonomy plateaus as fleets grow. Interventions rise, throughput stalls, and new models can’t deploy without months of lead time.
Nectar is filling the missing 40% of productivity.
There is no purpose-built compute layer between the cloud and the robot. That’s the gap Nectar fills.
Robot fleets are scaling faster than the infrastructure to support them.
WHY NOW
TREND 1
Transformer-based perception and planning models now demand 10–100× the FLOPs of 2022 baselines. On-robot GPUs can’t keep up without thermal, weight, and cost penalties.
TREND 2
A 100-robot warehouse generates petabytes monthly. Cloud round-trips add 50–200 ms latency — unacceptable for pick-and-place SLOs under 30 ms.
TREND 3
Today there is no purpose-built compute layer between the cloud and the robot. Warehouses lack the GPU density, cooling, and orchestration to run fleet-wide inference on-site.
SOLUTION
One Box on-site runs the heavy AI for the whole fleet. Robots keep only safety-critical motion onboard.
THE BOX — 27ft³ Immersion-Cooled GPU Node. Deployed on-site. Runs multi-camera perception, semantic understanding, and planning for every robot on the floor.
THE BRAIN — Fleet Orchestration Software. Schedules workloads, integrates with your stack (EKS Anywhere, Azure Arc, Terraform), supports multi-tenant sharing.
THE FLYWHEEL — Inference by Day, Training by Night. Idle compute becomes an asset—not a cost center.
PILOT PROGRAM
One site. One Box. One use case. Prove the ROI, then expand.
How does the Nectar Box differ from cloud GPU?
The Box deploys GPU compute directly on-site at your facility. Your AI workloads run with sub-25ms latency instead of 200ms+ cloud round-trips, which is critical for real-time robot fleet operations.
What hardware powers the Nectar Box?
Each Box is a 27 cubic foot immersion-cooled GPU node with enterprise GPUs, NVMe storage, and redundant networking. It installs alongside existing infrastructure with standard power and connectivity.
How long does deployment take?
A typical pilot deployment takes 90 days from contract to production inference. We handle hardware provisioning, on-site installation, and integration with your existing robot fleet software stack.