Industrial AI hardware platform for vision, robotics, and edge compute.

TUWA delivers AI camera modules, NPU compute boards, BSP firmware, and deployment tooling. From board bring-up to mass production, we help teams ship reliable AI hardware faster.

Start a Project Explore AI Hardware

0.5 to 8 TOPS NPU options across product tiers

MIPI / USB / GigE Camera and sensor interface support

BSP + SDK Linux bring-up, drivers, and OTA tools

NPU SoC Camera + ISP BSP + SDK

AI hardware product family for edge inference

From sensor capture to model execution and remote maintenance, each block is built for production hardware programs.

AI Vision Modules

Integrated camera + ISP + NPU modules for on-device detection, tracking, and event classification.

FPGA & Co-Processing

Programmable acceleration path for custom pre-processing, deterministic timing, and protocol bridging.

Remote Device Control

Out-of-band control, diagnostics, and fleet recovery for distributed AI hardware deployments.

Bring-up & Validation Kit

Carrier boards, debug tools, thermal accessories, and cables for fast lab-to-field validation.

Model Toolchain & SDK

Quantization, model conversion, runtime SDK, and OTA workflow matched to edge AI hardware constraints.

AI hardware architecture and delivery process

Clear hardware layers plus a production workflow designed for sensor integration, firmware stability, and scalable rollout.

Reference AI Hardware Stack

Sensing LayerMIPI/USB/GigE cameras, ISP tuning, and signal conditioning

Inference LayerNPU/CPU/FPGA compute boards with quantized model runtime

Control LayerGPIO/UART/CAN/RS485 integration for PLC and machine interfaces

Operations LayerOTA updates, watchdog telemetry, and remote diagnostics

Hardware Delivery Workflow

01 ScopeDefine sensor, TOPS, latency, power, and I/O requirements

02 Bring-upBoard init, BSP porting, driver validation, and baseline benchmarking

03 VerifyThermal, EMC, long-run stability, and model accuracy tests

04 ProductionDFM handoff, supply planning, and multi-site deployment rollout

AI hardware deployment proof

Real-world programs measured by hardware outcomes: latency, precision, uptime, and time-to-production.

Electronics EMS Factory Program False-defect calls -31% in 90 days

Inline AOI Upgrade with NPU Camera Nodes

Context: 12 SMT lines, 18 camera points, mixed lighting conditions, and strict response requirements on each station.

Implementation: on-device inference modules, PLC trigger integration, and buffered edge storage with scheduled sync.

3 weeksPilot to first line go-live

1.9xBoard triage throughput

96.8%Precision on defect classes

Robotic Picking Cell Hardware Retrofit

Replacing cloud vision with local NPU boards reduced pick confirmation latency from 180 ms to 95 ms in a 6-robot line.

Substation Thermal AI Camera Rollout

A 42-site deployment of low-power thermal AI cameras and event upload cut routine truck rolls by 38% in 4 months.

Retail Edge Vision Appliance Deployment

Across 57 stores, edge AI appliances lowered cloud bandwidth by 61% and reduced audit labor by 29% in the first quarter.

Partner Network

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Ready to define your AI hardware platform?

Share your sensor type, model workload, interface needs, and deployment scale. We will propose the right AI hardware architecture and delivery plan.

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