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Hardware-enforced artificial intelligence

We don't just need AI for everything.
We need trustworthy AI for everything.

As AI agents take physical form in robots, vehicles, and critical infrastructure, software-only defenses cannot keep pace. AGIACC embeds deterministic safety into silicon, ensuring autonomous systems fail safely by design.

Aligned with the capability-safety ecosystem

Arm Morello Microsoft CHERIoT UK DSbD CHERI Alliance RISC-V International
agiacc — safety-native stack
From hardware root of trust to embodied AI at scale: deterministic safety before autonomy reaches the physical world

Memory safety and compartmentalization, enforced directly in silicon.

01 // Spatial safety

Hardware capability bounds

CHERI capabilities replace raw pointers with unforgeable, bounded tokens. Buffer overflows, use-after-free, and pointer injection are stopped deterministically at the hardware level — not probabilistically detected by software heuristics.

CHERI-style hardware capabilities: bounded authority stops invalid memory access before damage spreads
02 // Isolation

Architectural compartmentalization

Each AI subsystem runs inside a hardware-backed compartment with explicit boundary policies. Breaches physically cannot propagate laterally, eliminating massive blast radiuses that plague current AI deployments.

Hardware-backed compartments for inference, plugins, and controls: no lateral privilege escalation by design
03 // Provenance

Trusted AI lifecycle

From data ingestion to model inference, every asset is governed by hardware-enforced access control. Prompt injection and model extraction mitigations are anchored in the infrastructure boundary.

04 // Root of trust

Chip-to-cloud verification

Trust is established from silicon boot and cascades upward. Built-in cryptographic engines and capability registers anchor the entire chain of custody for massive autonomous fleets.

05 // Performance

Zero-cost security

By shifting security primitives from software overhead to the processor pipeline, AGIACC achieves unparalleled safety guarantees without compromising the latency required for real-time robotic inference.


Software is failing autonomous vehicles and robots.

21.8×
Increase in AI security incidents since 2022 (OECD)
70%
Of vulnerabilities stem from memory safety issues
135K
Exposed embodied agent instances online currently
$4T+
Projected embodied AI market capitalization by 2030

The OpenClaw lesson

In 2026, the OpenClaw AI agent system demonstrated that when AI gets physical form, vulnerabilities become kinetic dangers. Over 135,000 instances were compromised due to legacy software flaws allowing remote code execution.

Bolting software patches onto fundamentally insecure architecture is a losing battle. We must embed safety directly into the processing layer.

Read the research