🧠Technology Overview

BytenovaAI Core Innovations

Containerized Edge AI Framework

• Lightweight AI Agents: Deploy models in isolated containers across edge nodes, enabling local training and inference without cloud dependency.

• GPU Orchestration: Dynamically allocate compute resources based on real-time demand, reducing costs by 40% compared to centralized cloud solutions.

Unified API & Protocol Layer

• Single Interface Control: Simplify integration with a unified API for managing AI workflows across clouds, edge nodes, and mobile endpoints.

• Protocol-Driven Scheduling: Automate resource allocation and task prioritization using decentralized governance mechanisms.

Hardware-Agnostic Acceleration

• Supports GPU, TPU, FPGA, and NPU architectures, ensuring compatibility with diverse AI applications in healthcare, manufacturing, and IoT.

Secure Multi-Party Computation (SMPC)

• Collaborate on model training without exposing raw data, leveraging encrypted channels and federated learning frameworks.