Making robots smarter and more efficient
The on-site AI datacenter for robot fleets — real-time fleet inference plus off-shift training, delivered as a managed service. Starting with warehouses and industrial inspection fleets.
Backed by
CHALLENGE
The robot autonomy ceiling
Compute doesn't scale with the fleet
Each robot streams 10–100+ Mbps of sensor data. A 50–200 robot site becomes a mini-datacenter overnight — but per-robot GPUs can't keep up.
Cloud adds jitter, not reliability
Backhaul latency is unpredictable. Tail-latency spikes miss SLOs, increase interventions, and erode throughput — especially at peak.
Per-robot GPU stacks are expensive
Duplicating high-end compute on every robot raises CapEx, heat, and field failure rates. Retrofits are slow and thermally constrained.
Autonomy plateaus as fleets grow
Interventions rise, throughput variance becomes the hidden tax, and new models can't deploy without months of lead time for capacity.
SOLUTION
On-site AI infrastructure, purpose-built for robot fleets
NECTAR BOX
Rugged on-site mini datacenter
~1 m³ immersion-cooled enclosure, 10–15 kW thermal budget. Shared GPU capacity for fleet inference during shifts and training off-shift. Installs alongside existing infrastructure.
NECTAR BRAIN
Telemetry-driven fleet orchestration
RL-based control plane that places, batches, and caches workloads across the Box. Learns from fleet traces to stabilize p95 latency, maximize GPU utilization, and reduce interventions.
DUAL-USE
Inference by day, training by night
Same GPUs serve real-time fleet inference during shifts and fine-tuning/retraining off-shift. Maximizes utilization and ROI without separate training infrastructure.
SAFETY-FIRST
Control stays on-robot, always
Safety-critical control loops remain on-robot. If connectivity drops, robots fall back locally and Box workloads degrade gracefully. No rip-and-replace required.
WHY NOW
The fleet is scaling. The infrastructure isn't. That's where we come in.
TREND 1
Foundation models outgrow on-robot hardware
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
Fleet-scale AI demands fleet-scale compute
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
No edge infrastructure exists for fleet-scale AI
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 — forcing operators to choose between unacceptable cloud latency and unscalable on-robot hardware.
Elastic OPEX Compute Tier
No robot retrofits. Scale with demand vs. rigid per-site GPU capex.
Dual-use GPU ROI
Inference by day + training off-shift.
Built for bursty fleets
Hundreds of robots → peak inference throughput. Warehouses & industrial sites with 6-7 figure ACVs per site.
PRICING
Simple, transparent pricing
Pick the plan that fits your team. No hidden fees. No contracts. Just protection.
Starter
Ideal for early-stage builders who want to launch fast with enterprise-grade protection.
$19 /month
✓ Basic protection
✓ 1 project
✓ Email alerts
✓ Manual scans
✓ Community support
Train in the cloud. Decide at the edge.
Deploy in one click. No setup. No stress.
Frequently asked questions
How does Nectar differ from a public cloud GPU?
Nectar deploys GPU compute directly at the telecom edge — inside carrier-neutral facilities — so your AI workloads run closer to end-users with lower latency, better data locality, and no egress fees.
What hardware powers the Nectar Box?
Each Nectar Box is a liquid-cooled, NEBS-ready micro data center with enterprise GPUs, NVMe storage, and redundant networking — designed for 24/7 telecom-grade reliability.
Can I scale up after starting with one box?
Absolutely. Nectar's CaaS model is elastic — add boxes on-demand as your fleet grows. Our orchestration layer handles workload distribution, failover, and capacity planning automatically.
Get in touch
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