Use Case · Edge & Physical AI
Intelligence at the point of action.
Run models where the data is generated. NVIDIA Jetson-based edge nodes, IoT integration, fleet OTA, sub-10 ms inference, and Isaac ROS for robotics — managed from the same Yobibyte control plane that runs the core cloud.
< 10 ms
On-device inference
300+
PoP fleet under management
275 TOPS
Jetson AGX Orin per node
5–60 W
Power envelope
Why teams struggle
The problems that block the work.
We hear the same pattern of failure modes across every engagement. These are the ones Yobitel exists to remove. Not generic platitudes, but the specific frictions that stall delivery.
Cloud round-trips kill latency
Camera → cloud → inference → action takes 200+ ms over 4G. The safety stop fires after the impact. The defect ships off the line. The cloud was always the wrong place.
Intermittent connectivity
Offshore rigs, agricultural sites, retail backrooms, vehicle fleets — they spend half the day off-network. A model that requires a TLS handshake to the cloud is no model at all.
Fleet management at scale
Three hundred edge boxes in twelve countries on six hardware revisions, six firmware versions, four model variants. Updates over USB stick are not a strategy.
Power and thermal envelope
Battery-powered cameras, solar-powered livestock collars, fan-less roadside cabinets. Cloud-grade models don't fit the wattage budget — and frying the SoC is not an option.
What Yobitel delivers
The capabilities we ship, end to end.
Each capability is a first-class product surface, not a slide. They compose into the platform behind every Yobitel customer in production.
NVIDIA Jetson platform
Reference designs and validated images for Jetson Orin Nano, Orin NX, and AGX Orin — up to 275 TOPS on-device for high-throughput edge inference.
Computer vision at the edge
Real-time detection, tracking, segmentation, and OCR for manufacturing QA, retail analytics, perimeter security, and traffic systems.
IoT & industrial protocols
MQTT, OPC-UA, Modbus TCP, BACnet, and CAN bus connectors. Sensor fusion across cameras, lidar, IMUs, and PLCs into a single inference pipeline.
Sub-10 ms inference
TensorRT optimisation, INT8/FP8 quantisation, layer fusion, and engine caching tuned per SKU. Predictable tail latency under thermal throttling.
Secure boot & SBOM
Hardware root of trust, encrypted dm-verity rootfs, signed kernel and model artefacts, and SBOM tracking on every firmware build.
Fleet OTA updates
Differential firmware and model updates across thousands of devices, with staged rollout, automatic rollback, A/B slots, and offline queueing.
Physical AI / robotics
Isaac ROS integration for AMRs, manipulators, and inspection robots. Sim-to-real with Isaac Sim, deployed onto Jetson with the same Yobibyte CI/CD.
Power-optimised profiles
5 W to 60 W power profiles for battery, solar, and constrained deployments. DVFS policies and workload schedulers tuned to thermal envelopes.
How adoption unfolds
From pilot to production, step by step.
The typical adoption path. We compress it where you have momentum and we slow it down where compliance or change-control demand it.
Pick the hardware & form factor
Yobitel engineers spec the Jetson SKU, enclosure, and IO for the deployment envelope — from solar-powered to in-vehicle to industrial DIN-rail.
Optimise the model
Quantise to INT8/FP8, fuse layers, build TensorRT engines, validate accuracy on representative edge data — all reproducible in the registry.
Deploy to a pilot fleet
Provision a 10–50 device pilot via Yobibyte edge. Telemetry, model artefacts, and policy enforced from the same control plane as the core cloud.
Scale to the production fleet
Staged OTA rollout to thousands of devices with cohorting, canary, and automated rollback. Offline-queued deltas for intermittent links.
Operate & iterate
Drift detection, edge eval gates, and re-training loops pull anomalies back into the central registry. The fleet keeps getting smarter.
The Yobitel stack behind this
Products & services that do this work.
No abstractions, no hand-waving. Each item below is a real Yobitel product or service with its own documentation, pricing, and SLA.
Yobibyte Edge Deploy
The same control plane manages cloud and edge — registry, OTA, telemetry, and policy across both surfaces.
Edge AI Infrastructure
Hardware reference designs, enclosures, networking, and power for production edge deployments.
AI Applications · Livestock Monitor
Production reference for solar-powered, intermittently-connected computer vision at scale.
Custom AI Solutions
Yobitel engineers co-design the model, hardware, and fleet ops for novel physical-AI deployments.
InferenceBench
Edge-specific eval suites: accuracy under quantisation, latency under thermal load, regression on representative scenes.
Outcomes we measure
The numbers customers report back to us.
Aggregated medians across recent deployments. Specific outcomes depend on workload and starting baseline. We'll model yours during the first conversation.
< 10 ms
On-device inference, no cloud round-trip
300+
Edge PoPs and devices under fleet management
99.5%
OTA rollout success rate with auto-rollback
70%
Lower bandwidth via on-device pre-filtering
Customer story
Precision-agriculture operator, livestock telemetry fleet
Solar-powered Jetson nodes monitor 14,000 head of cattle across rural sites with patchy connectivity. 96% anomaly-detection precision, sub-2 W average draw per node.
We needed AI that worked without a cell tower. Yobitel's edge stack is the only thing we found that genuinely does.
Where this lands
< 10 ms
On-device inference, no cloud round-trip
300+
Edge PoPs and devices under fleet management
99.5%
OTA rollout success rate with auto-rollback
Other use cases
Explore the rest of the solution suite.
Enterprise AI Operations
Deploy AI at Scale
Multi-tenant model serving, GPU fleet orchestration, governed rollouts, and end-to-end cost attribution — on one platform. Move from notebooks to a hardened control plane with model registry, canary deploys, and per-tenant FinOps built in.
ExploreInfrastructure Modernisation
Modernize Data Centres
Refit aging facilities into AI factories without ripping out what works. Yobitel engineers retrofit cooling, fabric, and orchestration around your existing footprint — then layer GitOps and platform tooling so the new estate runs itself.
ExploreApplied AI Engineering
Build AI Applications
Yobitel ships a complete app-building stack: typed SDKs, RAG primitives, agent orchestration, embeddable UI, and one-click deploy onto Yobibyte. Your product team focuses on the experience — we handle inference, observability, and the unglamorous middle.
ExploreAIOps & SRE Automation
Automate IT Operations
Anomaly detection, self-healing runbooks, GitOps drift control, and an AI SRE that triages incidents at machine speed. Yobibyte's automation surface plugs into your existing observability stack and learns from every postmortem.
ExploreReady to put this into production?
Talk to a Yobitel engineer. We'll map your environment, sketch the architecture, and propose a 60–90 day plan to first measurable outcome.