For more than three decades, Corvalent has built its reputation on rugged, long-life industrial computing hardware — the kind of gear that keeps running in oil fields, defense installations, and hospital equipment rooms for a decade or more without a hiccup. Its newest product line, CoreAI, takes that same philosophy of reliability and applies it to one of the fastest-moving areas of technology: artificial intelligence at the edge.
Why Industrial AI Needs a Different Approach
Consumer and enterprise AI tools are generally optimized for broad, general-purpose tasks — chatbots, web search, document summarization. Industrial environments call for something narrower and far more demanding: systems that can process data from sensors, PLCs, SCADA networks, and machine vision cameras in real time, often in dusty, vibration-heavy, or temperature-extreme settings where a cloud connection isn’t guaranteed or fast enough. Corvalent designed CoreAI specifically for that gap — turning raw operational data into decisions on the spot rather than shipping it off to a data center first.
The Hardware Behind CoreAI
Rather than building a single AI appliance, Corvalent has embedded CoreAI capability across its existing hardware families, giving customers a choice of form factor depending on where the intelligence needs to live:
- CoreAI Box PC — A compact 7.5-inch unit built around Corvalent’s Mini-ITX motherboards, with expansion slots for PCIe or PCI cards and I/O add-ons. It’s aimed at manufacturing and process-control tasks like visual inspection and predictive maintenance.
- CorSys Rackmount System — A full 19-inch rackmount platform rated for up to 15 years in production, suited to higher-throughput deployments in energy, defense, and critical infrastructure settings such as power forecasting and grid maintenance.
- CorGrid Edge Device — A compact, energy-efficient gateway built to plug directly into Corvalent’s CorGrid IoT platform, combining wireless and industrial communication protocols (Zigbee, LoRa, NB-IoT, satellite) with on-device inference — well suited to telemetry and diagnostics in aerospace and defense applications.
Each of these can be configured with Hailo AI accelerator modules, capable of up to 104 TOPS (tera-operations per second) at low power draw, or with NVIDIA GPU cards for heavier workloads. Corvalent has also begun offering the newer Hailo-10H module, which adds generative AI support in the same compact, power-efficient form factor.
What It’s Used For
CoreAI is positioned less as a single product and more as a toolkit that gets applied across a wide range of industrial use cases, including:
- Smart cameras and video analytics — facial recognition, license-plate reading, and anomaly detection for security, plus queue monitoring and theft detection in retail settings
- Manufacturing and automation — automated defect detection, predictive maintenance, and support for autonomous robotics on factory floors
- Smart cities and infrastructure — traffic and pedestrian monitoring, perimeter security, and AI-driven building energy management
- Telecom and 5G — local data processing at the network edge to cut latency, plus AI-assisted network optimization
- Robotics and drones — real-time navigation, mapping, and crop or pest monitoring for agricultural drones
The Bigger Picture
CoreAI reflects a broader shift happening across industrial computing: AI processing is moving out of centralized data centers and onto the machines and gateways closest to where data is generated. By building AI acceleration directly into hardware it already manufactures with a 7-to-15-year production guarantee, Corvalent is essentially offering customers a way to add modern AI inference to environments that can’t tolerate short product lifecycles or unpredictable cloud dependency — a niche that plays directly to the company’s long-standing strengths in long-life, mission-critical computing.
Learn more or request a quote at corvalent.com/contact.