AI is required to assess AI-powered autonomous systems.
General Autonomy modernizes verification, validation, hazard analysis, and cybersecurity for safety-critical autonomy. Our platform helps engineering teams cover more of the operational domain, trace every requirement, and reach certification faster.
ISO 26262 · ISO 8800 · ISO/PAS 21448 (SOTIF) · ISO/SAE 21434 · UL 4600
Physical AI
Safety engineering for the Physical AI era
Physical AI is the generation of systems that perceive, decide, and act in the real world: vehicles, robots, drones, and industrial machines. When these systems fail, the consequence is physical, not a stack trace on a screen. As foundation models and end-to-end learning move from the lab into embodied products, capability is outpacing our ability to prove safety.
General Autonomy is the safety layer for Physical AI. We assess the full perceive, decide, and act loop, wherever a learning-based system meets the physical world.
- Perception you can trust, validated against the long tail of real conditions
- Decisions you can defend, traced from hazard to evidence
- Actions you can certify, aligned with functional safety standards
- One assessment loop across every embodied domain
Physical AI closes a perceive, decide, and act loop with the world. We assess every stage of it.
The problem
Manual safety engineering cannot keep pace with AI-driven autonomy
Learning-based perception and planning operate across an effectively unbounded operational domain. The hazards that matter live in the long tail, far beyond what document-driven analysis and hand-built test suites can reach. Assessing systems of this complexity demands tooling of comparable capability.
Unbounded operational domain
Edge cases multiply faster than engineers can enumerate them. Coverage gaps become residual risk that surfaces only in the field.
Document-driven workflows
HARA, FMEA, and safety cases live in spreadsheets and disconnected documents. Traceability erodes with every requirement change.
Compressed certification timelines
Programs ship on aggressive schedules while assessment effort scales with system complexity. The bottleneck is engineering hours, not intent.
Our approach
AI to assess AI, with engineers in control
General Autonomy applies purpose-built AI to the assessment loop itself: analyzing the system, generating the scenarios that expose its weaknesses, and assembling the evidence that proves it is safe. Every output is structured, traceable, and reviewed by your engineers.
- Automate the repetitive drafting in hazard and cybersecurity analysis
- Generate risk-driven scenarios that target coverage gaps
- Maintain end-to-end traceability from hazard to evidence
- Keep humans accountable for every safety decision
A continuous assessment loop: analyze the system, generate scenarios that challenge it, and produce reviewable safety evidence.
Agent Studio
Build traceable AI agents that assist your system engineers
Compose safety agents from one dashboard. Each agent ingests your requirements, design specifications, or test data, reasons against the standard you assign it, and records a defensible trace from every conclusion back to its source.
Inputs
- Requirements
- Design specifications
- Test data
Agents 5 active
- Requirements AnalysisISO 26262 Done 142 requirements parsed · 3 safety goals derived
- SOTIF ScenarioISO 21448 Running Exploring ODD · 1,240 scenarios generated
- AI Safety AssuranceISO 8800 Running Evaluating ML component against 58 design specs
- Cybersecurity TARAISO/SAE 21434 Done 18 threats identified · 12 controls mapped
- Autonomy Safety CaseUL 4600 Queued Awaiting evidence from 2 upstream agents
Traceability
- Requirement to evidence REQ-142→HAZ-014→SG-07→TC-231
- Coverage gap to test ODD gap→S-088→TC-204
231 tests linked to hazards
Compose
Connect your requirements, design specifications, and test data, then assemble the agents your program needs.
Assign a standard
Bind each agent to ISO 26262, ISO 8800, ISO 21448 (SOTIF), ISO/SAE 21434, or UL 4600.
Run in the loop
Agents analyze the inputs, surface gaps, and draft work products for engineers to review.
Trace and certify
Every result links back to its source, producing an audit-ready trail your assessors can follow.
The platform
One safety engineering system, three products
G-Assess, G-Sim, and G-Data share a common model of your system, so hazards, scenarios, and evidence stay connected across the entire safety lifecycle.
G-Assess
AI safety engineering copilot for HARA, STPA, FTA, FMEA, TARA, safety goals, requirements traceability, and safety cases.
Explore G-AssessG-Sim
AI-powered scenario generation, digital-twin validation, simulation orchestration, edge-case discovery, and coverage analysis.
Explore G-SimG-Data
Safety data management, scenario libraries, synthetic data, ground-truth management, coverage metrics, and safety analytics.
Explore G-DataA shared safety model keeps hazards, scenarios, and evidence connected from concept through certification.
Engineering outcomes
Measurable impact across the safety lifecycle
The platform is built to move the metrics your program is judged on: effort, coverage, traceability, and time to certification.
Representative target outcomes. Results vary by program, system complexity, and integration depth.
Solutions
Built for the analyses safety engineering actually runs on
Verification & validation
Requirements-driven V&V planning, execution, and coverage tracking.
Hazard analysis
HARA, STPA, FTA, and FMEA with structured, reviewable outputs.
Cybersecurity analysis
TARA and threat modeling aligned with ISO 21434.
Scenario generation
Risk-driven, edge-case scenarios for simulation and test.
Digital-twin evaluation
Validate behavior against high-fidelity twins at scale.
Coverage analysis
Quantify what your operational domain testing actually covers.
Safety cases
Assemble structured, auditable safety-case documentation.
Requirements traceability
Link hazards, requirements, tests, and evidence end to end.
Industries
For the organizations building embodied autonomy
From automotive OEMs and Tier-1 suppliers to robotics and defense programs, safety-critical teams use General Autonomy to assess systems they can defend.
Why General Autonomy
An engineering platform, not a black box
Engineering-first
Built by and for functional safety, V&V, and cybersecurity engineers. The workflows mirror how certification actually works.
Standards-aligned
Outputs map directly to ISO 26262, ISO 8800, SOTIF, ISO/SAE 21434, and UL 4600 work products, so evidence is audit-ready by construction.
Human-in-the-loop
AI accelerates the work; your engineers own every safety decision. Nothing reaches a safety case without review.
Traceable by design
Every hazard, requirement, scenario, and test links to its evidence, with a defensible audit trail.
Multi-domain
One platform spanning automotive, robotics, industrial, and defense autonomy, not a single-vertical point tool.
Deployment-flexible
Integrates with your existing toolchain and data, with options for isolated and on-premise deployment.
See General Autonomy on your safety program
Book a technical walkthrough with our safety engineering team. We will map the platform to your standards, systems, and certification timeline.