01 / Smart Manufacturing
Industrial Automation & Inspection
Power real-time defect detection, predictive maintenance, PLC coordination, and multi-sensor fusion directly on the factory floor.
High-Throughput Edge AI↗
Scalable Compute · Edge AI
Multi-Level Edge AI Platforms
Right-size your edge intelligence. IntelliGienic delivers a scalable portfolio of Edge AI computing platforms—from low-power embedded modules to high-performance industrial AI systems—built to match your workload, power budget, and deployment environment.
✓ Scalable TOPS Performance
✓ Power-Efficient Architectures
✓ Application-Ready SDKs
Multi-tier computeRight-sized AI performanceOptimized SWaP-C ↗
mW—WDesigned to scale from milliwatt endpoint AI nodes to high-throughput multi-stream edge servers.
Multi-Level Edge AI
Match Every Workload with the Right Compute Tier.
Not every AI application requires the same compute envelope. Our multi-level Edge AI platforms span entry-level AIoT modules, mid-range System-on-Modules (SoMs), and ruggedized high-TOPS edge computers—enabling teams to balance inference throughput, thermal constraints, I/O flexibility, and total system cost.
- Tiered compute from entry TOPS to high-TOPS
- Heterogeneous CPU, GPU, and NPU acceleration
- Flexible SoM, SBC, and Box PC form factors
- Rich industrial I/O and sensor interfaces
- Unified model deployment and SDK toolchains
- Thermal and power-optimized industrial design
Core Capabilities
Compute Architectures Built to Scale.
Deploy AI models efficiently across diverse product tiers with hardware and software capabilities designed for flexibility, reliability, and long-term lifecycle support.
Select a capability to explore how it can support your product or deployment.
Select the ideal performance tier for your application—from lightweight microcontrollers and entry-level NPUs for sensor fusion and smart endpoints, to high-performance edge AI systems capable of running complex multi-model and generative AI workloads.
Leverage integrated NPUs, GPUs, DSPs, and multi-core CPUs to distribute workloads efficiently. Offload neural network inference to dedicated accelerators while keeping general system control, preprocessing, and communication responsive.
Accelerate product development with modular System-on-Modules (SoMs), custom carrier boards, single-board computers (SBCs), or deployment-ready industrial Box PCs. Transition smoothly from rapid prototyping to volume production.
Connect seamlessly with cameras, LiDAR, radar, industrial buses, and high-speed network interfaces including MIPI-CSI, USB, Gigabit Ethernet, PoE, CAN bus, and PCIe to support complex edge aggregation and real-time control.
Simplify model quantization, compilation, and deployment with support for mainstream AI frameworks and hardware-optimized SDKs. Reduce engineering overhead when scaling or migrating models across different platform performance tiers.
Operate reliably in constrained or harsh environments with fanless thermal designs, wide-temperature component options, and optimized performance-per-watt profiles tailored for continuous 24/7 edge operation.
From Concept to Deployment
One Cohesive Platform Path.
Move from workload evaluation to field deployment with a structured approach to hardware sizing, software optimization, and system integration.
STEP 01
Profile
Evaluate AI model complexity, target latency, sensor inputs, and SWaP-C (Size, Weight, Power, and Cost) requirements.
STEP 02
Select
Choose the optimal compute tier and form factor—from compact embedded SoMs to ruggedized Edge AI Box PCs.
STEP 03
Optimize
Quantize, compile, and accelerate neural networks using hardware-matched SDKs and runtime inference engines.
STEP 04
Deploy
Integrate cameras, sensors, and industrial I/O, validate thermal reliability, and scale into production applications.
Application Scenarios
Powering Intelligence Across Industries.
Adaptable Edge AI computing platforms engineered for environments where local processing, low latency, and operational reliability are critical.
02 / Autonomous Systems
Robotics, AMR & Mobility
Deliver low-latency perception, SLAM navigation, obstacle avoidance, and motion control within strict onboard power budgets.
SWaP-Optimized Compute↗
03 / Smart Infrastructure & AIoT
Smart Spaces, Retail & Gateways
Enable multi-stream video analytics, intelligent traffic management, interactive kiosks, and secure local data aggregation.
Scalable Edge Gateways↗
Explore the Ecosystem
Choose the Right Edge AI Building Blocks.
Explore compute platforms and complementary sensing options that can be configured into a complete multi-level Edge AI solution.
USB Cameras
Plug-and-play imaging interfaces for Edge AI box PCs, rapid development, and machine vision.
Explore Products ↗MIPI Cameras
Direct low-latency camera modules for embedded SoMs, SBCs, and compact Edge AI designs.
Explore Products ↗Thermal Cameras
Radiometric and thermal imaging inputs for multi-modal edge analytics and condition monitoring.
Explore Products ↗Laser Sensors
Precision distance and spatial sensing to complement Edge AI perception in robotics and automation.
Explore Products ↗Smart Cameras
All-in-one Edge AI vision nodes combining onboard compute and imaging in a single unit.
Explore Solutions ↗Frequently Asked Questions
Selecting Your Edge AI Platform?
Every application balances model complexity, inference speed, thermal limits, and hardware interfaces differently. Start with your target workload and deployment constraints.
Need help sizing your Edge AI compute platform? Share your target AI models, camera/sensor count, and operating environment with our team.
A multi-level approach offers a scalable range of hardware tiers—from low-power embedded modules to high-TOPS edge computers—allowing developers to right-size compute performance, power consumption, and cost for each specific application.
Selection depends on your neural network architecture, input resolution, required frame rate (FPS), number of concurrent sensor streams, and whether pre- and post-processing workloads run across the CPU, GPU, or dedicated NPU.
SoMs are ideal when you need a custom carrier board and compact footprint for volume production. SBCs accelerate prototyping and embedded integration, while rugged Box PCs provide enclosure-ready deployment for industrial environments.
Yes. Our team can assist with platform evaluation, peripheral and camera matching, carrier board customization, and AI model deployment across our supported Edge AI hardware ecosystem.
Let's Build What's Next
Power Your Application with the Right Edge AI Platform.
Tell us about your AI workload, sensor requirements, and deployment environment. Let's configure the optimal compute platform for your next product.
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