The Deterministic Edge Control System for Safety-Critical AI.

DECS is designed to validate every AI decision against predefined safety limits before actuation, enabling bounded, deterministic execution across heterogeneous edge platforms.

Edges AI Systems builds the Deterministic Edge Control System (DECS), a safety-grade platform comprising a deterministic secure boot loader, a Type-1 static-partitioning hypervisor, and a real-time runtime, with safety-critical layers architected for memory safety. DECS is designed to validate every AI decision against predefined safety constraints before actuation, enabling deterministic closed-loop control for safety-critical systems.

The DECS runtime and NPU layers have been demonstrated on an Arm-based development board and are designed for portability across heterogeneous SoCs from NVIDIA, AMD, Renesas, NXP, ST, and TI. Designed to support development aligned with IEC 62304, ISO 14971, ISO 26262, IEC 61508, and DO-178C. Flagship application: closed-loop medical neuromodulation.

Explore DECS Solutions Contact Us

Safety-Gated AISilicon-to-SoftwareSecure-by-DesignMemory-SafeReal-TimeSafety-Ready

Solutions

Production-grade technologies and engineering services that deliver and port DECS.

Silicon & Platform Engineering→

End-to-end silicon validation from RTL to production bring-up.

Key Capabilities

01Pre-silicon RTL verification and testbench development

02UVM-based functional verification strategies

03Coverage analysis and regression automation

04FPGA prototyping and emulation environments

05Firmware-assisted silicon validation

06Post-silicon bring-up and hardware debug

07Signal integrity and high-speed interface validation

08Performance characterization and stress testing

09Arm Cortex-A / M / R + NPU board bring-up — measured deterministic inter-processor messaging on the reference board (~88 µs round-trip floor, zero message loss) and from-scratch Arm Ethos-U NPU enablement

Boot Loader & Secure Boot→

Secure boot architecture and chain-of-trust implementation.

Key Capabilities

01Custom bootloader architecture and bring-up

02Secure boot and chain-of-trust enforcement

03Root of Trust integration

04Firmware signing and verification

05Anti-rollback protection

06Secure update frameworks

07DECS deterministic secure boot loader — single-stage integrity-verified boot (SHA-256) with a small, review-sized trusted computing base (~2 kLOC); host-tested, silicon bring-up in progress

Secure Hypervisor→

Secure, type-1 virtualization enabling deterministic partitioning.

Key Capabilities

01Type-1 hypervisor architecture and integration

02Static partitioning that isolates the AI path from the real-time control path

03Real-time partitioning and deterministic scheduling

04Mixed-criticality workload isolation

05Secure virtualization and hardware-assisted virtualization support (ARM VE, virtualization extensions)

06Inter-partition communication mechanisms

07Resource allocation and memory isolation

08Safety hypervisor host-tested, silicon bring-up in progress

09Safety-oriented system architecture support (ISO 26262 / DO-178C alignment)

Device Drivers & I/O Subsystems→

Production-grade driver and I/O subsystem integration.

Key Capabilities

01Linux kernel and RTOS driver development

02Interrupt handling and DMA optimization

03High-speed interface enablement (UCIe, PCIe, USB, Ethernet, CAN)

04Memory-mapped I/O and register-level integration

05Power management and low-latency tuning

06Middleware and hardware abstraction layer (HAL) integration

07Deterministic Cortex-A to Cortex-M messaging (OpenAMP / RPMsg) characterization and tuning — measured ~88 µs round-trip floor with a firmware-independent 0.117 µs/byte payload cost

08Performance profiling and real-time debugging

RTOS & OS Implementation→

Deterministic RTOS and OS integration for safety-critical embedded systems.

Key Capabilities

01RTOS and Linux porting

02Kernel customization and optimization

03Real-time scheduling and latency control

04Multi-core (SMP/AMP) architecture

05Memory protection and safety partitioning

06System hardening and performance tuning

07Linux, RTOS, and bare-metal coexistence under DECS — measured ~20% round-trip latency reduction from removing the RTOS on the control core (controlled same-board comparison)

Edge AI Embedded Systems→

Architecture-driven integration of AI workloads into embedded platforms.

Key Capabilities

01AI model deployment on embedded SoCs

02Hardware acceleration (NPU / GPU / DSP) integration

03Real-time inference optimization

04Memory and power footprint tuning

05Secure AI runtime integration

06Edge-to-cloud data orchestration

07Safety-gated inference architecture — validating AI decisions against safety constraints before actuation (the DECS design center)

08Closed-loop, control-theoretic edge control (real-time sense–infer–act loops)

09From-scratch NPU enablement: Vela / Arm Ethos-U bring-up demonstrated from scratch at 0.35–0.46 ms per inference, plus eIQ Neutron, Neural-ART, C7x-MMA, and train-on-NVIDIA-GPU / deploy-to-Jetson-with-TensorRT targets

HMI & GUI Systems→

Production-grade human–machine interfaces delivering responsive, secure, and real-time visualization.

Key Capabilities

01Industrial and medical HMI design

02Cross-platform GUI development (Qt / embedded Linux / Windows)

03Real-time monitoring and control interfaces

04Hardware-accelerated graphics integration

05Multi-display and touch interface support

06Performance optimization and system integration

07Real-time system-monitor HMI demonstrated on the reference board — touch-driven, hardware-accelerated, resolution-independent, running over Wayland (coexisting with the vendor HMI), direct DRM/KMS, or serial, and driving a live on-device latency probe

Edge-Cloud & IoT Platforms→

Cloud-native web architectures delivering secure, scalable, and production-ready digital systems.

Key Capabilities

01Frontend web application development

02Backend APIs and microservices

03Database architecture and optimization

04Cloud infrastructure (AWS / Azure / GCP)

05DevOps, CI/CD, and containerization

06Authentication and security architecture

Functional Safety & Certification→

Standards-aligned engineering ensuring safety compliance for regulated embedded systems.

Key Capabilities

01ISO 26262 ASIL D Compliance Support

02DO-178C Aerospace & Defense Alignment

03DO-254 (airborne hardware) and DO-160 (environmental) artifact preparation

04IEC 62304 medical software processes

05ISO 14971 medical risk management

06IEC 61508 industrial functional safety

07ISO 21434 cybersecurity integration

08Safety architecture and hazard analysis

09Traceability, documentation, and audit preparation

IoT Systems→

Secure, scalable distributed intelligence for connected devices.

Key Capabilities

01Device firmware and OTA mechanisms

02Secure communication stacks and encryption

03Gateway and edge node orchestration

04Telemetry aggregation and fleet analytics

05Cloud–Edge synchronization architectures

Technology

The core platform technologies inside DECS — secure, deterministic, and scalable edge systems.

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→

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

05Safety-gated inference: designed to validate AI decisions against safety constraints before actuation

06From-scratch NPU enablement — Arm Ethos-U person-detection demonstrated at 0.35–0.46 ms per inference (~2,900 inferences/s) on the reference board

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

05Bounded, closed-loop execution model (sense, infer, decide, act)

06Measured latency distributions (p50 ~106 µs idle at 96 B, ~136 µs under concurrent NPU-plus-GUI load; p90 ~137 µs idle, ~193 µs loaded; p99 ~157 µs idle, ~385 µs loaded), with zero errors and zero drops across 30,000+ messages

Safety-Oriented 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)

04Static partitioning that isolates the AI inference path from the real-time control path

05Strong memory isolation and fault containment

06Mixed-criticality workload separation (safety, control, AI, HMI)

07Secure boot integration and trusted execution support

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

04From-scratch NPU enablement, including the Vela model pipeline, on-device runtime, and live inference dashboard

05Deployment targets: Arm Ethos-U, Neural-ART, eIQ Neutron, C7x-MMA DSP, FPGA DPU / AI Engines, and NVIDIA Jetson (TensorRT)

Industries

Serving sectors where system integrity, security assurance, and safety-gated, closed-loop action are essential.

Semiconductor→

Reduce time-to-production and mitigate silicon validation risk — backed by measured bring-up proof points.

Industry Focus

01SoC bring-up acceleration

02Pre/post-silicon validation

03Secure boot enablement

04UCIe / PCIe interface integration

05From-scratch NPU enablement (Arm Ethos-U demonstrated; eIQ Neutron targeted)

Automotive→

Enable certification-aligned, secure multi-domain vehicle platforms.

Industry Focus

01ISO 26262 ASIL-D systems

02Mixed-criticality consolidation

03Secure OTA updates

04Zonal architecture

05Automotive Arm Cortex-A / Cortex-R platform targets (Cortex-R52 lockstep — portability designed)

Aerospace & Defense→

Deliver certification-aligned, secure, mixed-criticality avionics and unmanned-systems platforms.

Industry Focus

01Unmanned systems: partitioned UAV flight computers

02DO-178C DAL A/B software; DO-254 and DO-160 support

03Secure partitioned avionics

04Deterministic execution

05High-assurance boot chains

Medical→

Accelerate standards-aligned, secure, closed-loop medical platforms — adaptive, phase-locked therapy with predictable real-time behavior.

Industry Focus

01Closed-loop neuromodulation for Essential Tremor and Parkinson's

02Real-time phase-locked, adaptive stimulation (PLL + Extended Kalman Filter)

03Targeting sub-10 ms bounded end-to-end control, fully on-device — no cloud dependency

04Multi-modal sensing: fingertip IMU, multi-site EMG, skin impedance

05Medical software processes aligned with IEC 62304 and ISO 14971

Industrial Control→

Deliver secure, always-on industrial platforms with deterministic control and scalable AI-assisted operations.

Industry Challenges

01Deterministic real-time control

02Closed-loop automation and robotics (IEC 61508)

0324/7 uptime requirements

04Secure industrial networking

05Mixed-criticality consolidation (control + HMI + AI)

06Legacy system integration

Cloud Infrastructure→

Build secure, scalable edge-cloud platforms with predictable performance and automated operations at enterprise scale.

Industry Challenges

01Secure multi-tenant isolation

02Scalable distributed architectures

03Edge-to-cloud orchestration

04Low-latency data pipelines

05Infrastructure automation

About Edges AI Systems

Edges AI Systems is founded on the principle that intelligence must be engineered with assurance, not merely integrated.

Learn More

01Security by Design

02Deterministic Performance

03Safety-Gated AI

04Memory Safety

05Lifecycle Reliability

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For safety-critical, high-performance, and security-sensitive systems

Engage Edges AI Systems to architect, secure, and deliver deterministic embedded and Edge AI platforms — from silicon bring-up to real-world deployment.

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