Technology

Core platform technologies for secure, deterministic, and scalable edge systems.

Secure Boot & Root of Trust
01

Secure Boot & Root of Trust→

Hardware-anchored trust chain from first instruction.

Platform Architecture

  • 01Hardware Root of Trust architecture (eFuse, TPM, HSM, secure elements)
  • 02Chain-of-trust implementation from BootROM through OS
  • 03Cryptographic image signing and verification (RSA/ECC/SHA-2/3)
  • 04Measured boot and attestation support
  • 05Anti-rollback protection and secure version management
  • 06Secure firmware update frameworks (OTA-ready)
  • 07Key management and secure provisioning workflows
  • 08Trusted execution environment (TEE) integration
Edge AI Secure Kernel
02

Edge AI Secure Kernel→

Protected runtime foundation for AI at the edge.

Architecture Highlights

  • 01Deterministic real-time scheduling for AI inference workloads
  • 02Secure execution isolation and memory protection
  • 03Hardware acceleration integration (NPU / GPU / DSP)
  • 04Lightweight, resource-optimized runtime for edge deployment
Deterministic Runtime Architecture
03

Deterministic Runtime Architecture→

Predictable execution behavior under real-world load.

Architecture Highlights

  • 01Deterministic scheduling and bounded-latency execution
  • 02Memory isolation and partitioned resource management
  • 03Multi-core orchestration (SMP / AMP) with workload separation
  • 04Performance monitoring and real-time system diagnostics
Safety-Certified Hypervisor
04

Safety-Certified Hypervisor→

Partitioned virtualization aligned to safety goals.

Platform Capabilities

  • 01Certification alignment up to ISO 26262 (ASIL D) and DO-178C objectives
  • 02Deterministic real-time partition scheduling
  • 03Hardware-assisted virtualization (ARM virtualization extensions)
  • 04Strong memory isolation and fault containment
  • 05Mixed-criticality workload separation (safety, control, AI, HMI)
  • 06Secure boot integration and trusted execution support
Real-Time AI Acceleration Framework
05

Real-Time AI Acceleration Framework→

Low-latency AI execution path optimization.

Platform Capabilities

  • 01Real-time AI workload scheduling with bounded latency
  • 02Hardware accelerator integration (NPU / GPU / DSP) with optimized data paths
  • 03Low-latency inference pipelines and memory-efficient execution
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