Intigia implements Artificial Intelligence algorithms on SoC’s & FPGA’s or computer vision and advanced time series analysis applications.
Our team is experienced in partitioning deep learning models into embedded software and FPGA based hardware accelerators to meet the most demanding real time requirements.
We use real time deep learning inference on the edge for multiple applications:
- Predictive Maintenance: we develop systems that read data from sensors that measure the performance of industrial assets, process this data using deep learning techniques (LSTM, autoencoders) to detect anomalies and predict failures before they occur.
- Quality inspection based on computer vision: we develop systems that processes images using Convolutional Neural Networks (CNN) to detect defects and classify objects according to their physical features (size, shape, color)
Our team has developed multiple projects on FPGAs using OpenCV and Vitis AI for real time computer vision inferenced on Xilinx platforms.
Efficient methodologies for safety critical systems
Our methodology is designed to minimize pitfalls and risks early in the project while our automated quality assurance processes ensure to deliver steadily minimizing iterations.
We can adapt to each project needs from agile project management to safety critical standards (DO-254, ISO 26262, ESCC).
Intigia is a proud member of Xilinx Alliance. We have many years of experience implementing our designs on Xilinx devices (Virtex, Spartan, Kintex 7, Kintex Ultrascale, Zynq 7 and Zynq Ultrascale), on other FPGA vendors (Lattice and Microsemi) and ASICs.