IoT & Edge AI
Intelligent Devices That Make Money
Low-latency intelligence at the edge, with secure provisioning and fleet operations that scale from a prototype to thousands of devices in the field, resilient even when connectivity isn't.
Some decisions can't wait for the cloud.
The cloud is the wrong place to make a decision that has to happen in ten milliseconds on a factory floor. By the time sensor data makes the round trip, the defective part is already down the line, the machine has already failed, and the moment has passed. And the moment connectivity drops, a cloud-dependent device becomes an expensive brick.
Intelligence at the edge, operated at scale.
We push inference to where the data is born and design for the network not being there. Models run locally for millisecond decisions, buffer telemetry when offline, and sync when the link returns, so a dropped connection degrades gracefully instead of stopping the line.
Engineered to production standards.
- ML inference deployment via AWS IoT Greengrass and Azure IoT Edge
- Real-time, low-latency decision-making at the device
- Fleet management for thousands of devices with secure zero-touch provisioning
- Digital twins and over-the-air model & firmware updates
- Edge-to-cloud telemetry with offline-first resilience
- Purpose-built for manufacturing, healthcare, and logistics environments
“Real-time decisions at the device, with the fleet infrastructure to scale them.”
Built for production from day one, then handed over with the runbooks so the capability stays with your team.
- 01Real-time quality inspection on a production line
- 02Predictive maintenance from on-device sensor data
- 03Connected medical and logistics devices with offline resilience
- 04Fleet rollout with zero-touch provisioning and OTA updates
Battle-tested tools, chosen to fit your team and constraints, never technology for its own sake.
- AWS IoT Greengrass
- Azure IoT Edge
- Digital Twins
- OTA Updates
- MQTT
- Edge ML
Runs on
Your cloud account, your racks, or the edge.See the infrastructure behind it
Why teams pick us for this.
- 01
Offline-first by design
We assume the network will fail and build for it. Local inference and buffered telemetry keep devices working and lose nothing when connectivity drops.
- 02
Fleet operations, not just a prototype
Zero-touch provisioning, OTA updates with rollback, and digital twins make the jump from one device to ten thousand a plan rather than a crisis.
- 03
Edge-to-cloud as one system
We design the device, the sync, and the cloud backend together, so telemetry, updates, and security fit instead of fighting each other.
Answers before you ask.
Which platforms do you build on?
Primarily AWS IoT Greengrass and Azure IoT Edge, chosen to match your existing cloud and hardware. We run inference with the runtime that fits your device's compute and memory budget.
What happens when a device loses connectivity?
It keeps making decisions locally and buffers its telemetry, then syncs automatically when the connection returns.
How do you update models across thousands of devices?
Over the air, in controlled rollouts with rollback. You can stage an update to a subset of the fleet, verify it, then expand, the same way you would ship software safely.
Which industries do you work with?
Most often manufacturing, healthcare, and logistics, anywhere real-time decisions at the device unlock efficiency, safety, or new revenue.
More of what we do.
Ready to build the future together?
Tell us where you're headed. We'll map the fastest secure path from idea to production.