Wedoany.com Report on Feb 14th, Microchip Technology recently expanded its edge artificial intelligence (AI) product portfolio by introducing a full-stack solution designed to simplify the development of production-ready applications based on microcontrollers (MCUs) and microprocessors (MPUs). These devices, typically deployed at the edge for tasks such as real-time sensor data collection and actuator control, are now transformed into platforms that support intelligent real-time decision-making.
By integrating a full-stack combination of silicon, software, and tools, the company addresses challenges in edge AI related to performance, power consumption, and security, while improving implementation efficiency. Mark Reiten, Corporate Vice President of Microchip's Edge AI Business Unit, stated, "Edge AI is no longer experimental—it has become an expectation because it outperforms cloud-based implementations in many ways. We established the Edge AI Business Unit to combine MCUs, MPUs, and FPGAs with optimized machine learning models, model acceleration, and development tools to accelerate the design of secure and efficient intelligent systems."
The new full-stack application solutions include pre-trained deployable models and customizable application code, supporting implementation through Microchip's embedded software, machine learning development tools, or partner tools. Specific applications include: AI-based signal analysis for arc fault detection, condition monitoring for predictive maintenance, face recognition security authentication with liveness detection, and keyword recognition interfaces for consumer, industrial, and automotive sectors.
Engineers can leverage Microchip's development platforms, such as the MPLAB X integrated development environment and MPLAB Harmony software framework, to rapidly prototype and deploy AI models, reducing complexity and shortening design cycles. For FPGAs, the VectorBlox Accelerator SDK 2.0 platform accelerates compute-intensive workloads like vision and sensor analysis. Additionally, the company provides training tools such as motor control reference designs, complemented by complementary components like PCIe devices and high-density power modules, supporting edge AI applications in industrial automation and data centers.
According to an IoT Analytics market report from October 2025, embedding edge AI capabilities into MCUs is one of the industry's major trends, helping to reduce latency, enhance data privacy, and decrease reliance on cloud infrastructure. Microchip Technology reinforces this trend through its MCU, MPU, and FPGA platforms, driving the development of the edge AI ecosystem. The company is collaborating with customers to provide model training support and expanding software options with partners. More details are available on the official website.
