Aerbix Distributed AI Inference Platform
Enable low-latency AI inference, autonomous workflows, and intelligent device orchestration across industrial infrastructure, robotics, drones, and connected edge ecosystems.
Edge devices orchestrated across manufacturing, logistics, and autonomous fleets.
Average inference latency for mission-critical real-time edge decisions.
Technical Application Profile
Executive Overview
Aerbix is an Edge AI platform designed for building and deploying autonomous systems capable of processing data locally with minimal cloud dependency. The platform enables developers and enterprises to deploy AI-powered applications that perform real-time perception, decision-making, and automation across robotics, industrial monitoring, smart infrastructure, and IoT environments.
Our architecture is focused on low-latency AI execution, combining computer vision, multimodal sensor processing, and intelligent automation into a scalable edge-native platform. As our models continue to grow in complexity, GPU acceleration becomes essential for efficient training, optimization, and production inference.
Core Technical Stack
At the current stage, Aerbix is not yet integrated with NVIDIA SDKs in production. We are actively preparing our infrastructure to adopt NVIDIA's AI software stack as part of our production deployment roadmap.
NVIDIA SDK Roadmap
Optimize deep learning inference by compiling trained PyTorch models into highly optimized TensorRT engines.
Process high-volume video streams from cameras and edge devices for computer vision workloads.
Accelerate custom AI processing pipelines and computational workloads running on edge GPUs.
Centralize AI model serving with dynamic batching and standardized microservices for enterprise-scale inference.
Compute & Hardware
Our workloads involve large computer vision models, object detection, sensor fusion, autonomous decision-making, real-time inference, and continuous model fine-tuning. These require high memory bandwidth and substantial parallel compute capabilities. NVIDIA H100 Tensor Core GPUs provide the Transformer Engine, Tensor Cores, and HBM3 memory necessary to accelerate model training, optimize inference latency, and support production-scale deployments.