Engineering work across edge AI vision, embedded devices, system integration, and product readiness.
Development & Integration
Custom computer vision software development for embedded vision, Edge AI applications, connected devices, and product readiness.
Engineering Areas
Edge AI Vision
Edge Vision Systems
Embedded vision pipelines, on-device inference, and surrounding system work for computer vision products.
Mobile Vision Applications
On-device AI, vision-driven workflows, and mobile companion app & device experiences.
Training & Evaluation Data Systems
Data acquisition setups and supporting software used to train, test, and evaluate AI-driven systems
Embedded Device Engineering
Connected Embedded Devices
Device-side engineering across firmware, peripherals, RTOS, connectivity, and board-level integration.
OS, ISP & Board Support
Bring-up, adaptation, and support work across Linux, Zephyr, and platform-specific board support layers.
Hardware Prototyping
Sensor and embedded hardware prototyping, board bring-up, and early-stage technical validation.
Integration and Infrastructure
IoT & Connected Systems
Connectivity, telemetry, control, and system integration for devices that need to stay manageable in the field.
System & Cloud Integration
Backend and cloud-side engineering that connects device behavior to APIs, orchestration, and product workflows.
CI/CD & Validation Infrastructure
Build, test, deployment, and hardware-in-the-loop workflows that support repeatable engineering delivery.
Our Expertise
Vision-Capable Embedded Platforms
Working across embedded platforms used for vision workloads, including Ambarella, Hailo, NXP, Qualcomm, and Rockchip.
Sensor to Decision Pipeline
From sensor input and image pipeline work to on-device inference and the logic that turns recognition into action.
On-Device Inference
Getting computer vision workloads to run on the target device, with the surrounding system pieces in place.
Performance & Productionization
Improving latency, power, thermal behavior, and robustness before the product reaches the field.
Connected Vision Security
Supporting certifiability and cyber resilience work for connected vision devices, including CRA-related implementation needs.
Device Integration & Maintainability
Handling the device-side integration work that affects updateability, lifecycle reliability, and long-term maintainability.
Our Projects
How Teams Usually Start With Us
Discovery Sprint
Early work around constraints, hardware fit, integration risks, and delivery planning.
Discovery Sprint
Embedded Deployment Sprint
Focused work to get vision workloads running on target hardware.
Embedded Deployment Sprint
PoC Rescue / Productionization
For teams that have something working in prototype form but are stuck before production.
PoC Rescue / Productionization
How Development Projects Usually Run
Frame the scope
We align on the use case, target device, constraints, and what a realistic delivery path looks like.
01
Check hardware fit
We assess whether the platform can carry the vision workload across compute, memory, power, and thermal limits.
02
Bring up the system
We get the pipeline running on target hardware, from sensor and runtime integration to on-device inference.
03
Stabilize for product use
We work through latency, robustness, thermal behavior, and integration issues before rollout.
04
Prepare for life in the field
We support updateability, lifecycle reliability, and connected-device resilience & security.
05
Get in Touch
Have a project in mind? Let’s discuss how we can help you achieve your goals.