CoCoPIE Inc.

Founded 2020

Compress and compile machine learning models for deployment on edge devices

You can use CoCoPIE to compress, compile, and deploy artificial intelligence models across edge devices, mobile hardware, and cloud systems. The system links model compression directly with compiler code generation and runtime scheduling, ensuring models fit strict memory and latency boundaries without sacrificing accuracy. You can define target hardware specifications, automate model reduction, generate native executable code, and validate performance on actual target devices. This process turns resource-heavy neural networks into lightweight, production-ready code for local execution on phones, microcontrollers, and servers.

What CoCoPIE Inc. does

Define accuracy and latency constraints for neural network deploymentCompress neural network weights and architecturesCompile trained models into hardware-specific binary codeSchedule memory and compute workloads across target hardwareMeasure inference speed on connected test hardwareExport deployable packages for production integrationCompresses large neural networks for resource-constrained devicesGenerates native executable code tailored to target hardware architecturesCoordinates model compression, compiler transformations, and runtime scheduling togetherEvaluates model accuracy and latency directly on physical target devicesProvides on-premise private deployment options for secure environmentsSupports automated requirement-driven model reduction workflows