Saphira AI

A closed-loop platform that validates physical AI systems through hazard analysis, safety requirements, simulations, and certification evidence.

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About Saphira AI

Saphira AI provides a unified validation factory for physical AI systems, integrating hazard analysis, safety requirements, simulated scenarios, and certification evidence into a single closed loop. The platform is designed to streamline the validation process for AI-driven physical systems, ensuring compliance with safety standards and regulatory requirements. It supports developers, engineers, and compliance teams by automating the generation of safety cases and evidence, reducing manual effort and accelerating certification. Saphira AI is particularly useful for industries such as robotics, autonomous vehicles, and industrial automation where safety and compliance are critical. By consolidating hazard analysis, scenario simulation, and certification documentation, the platform helps teams achieve faster time-to-market while maintaining rigorous safety standards. It is built to address the unique challenges of validating AI in physical environments, where traditional testing methods may fall short.

Key features

Hazard analysis for AI systems
Safety requirements generation
Simulated scenario testing
Certification evidence automation
Closed-loop validation process
Compliance with safety standards
Integration with physical AI workflows
Automated safety case generation
Regulatory requirement tracking
Evidence documentation for certification

Use cases

Validating autonomous vehicle safety systems
Ensuring compliance for industrial robotics
Generating certification evidence for AI-driven medical devices

Pros

Unifies hazard analysis, safety requirements, simulated scenarios, and certification evidence into a single closed-loop platform
Automates generation of safety cases and evidence, reducing manual effort and accelerating certification
Supports traceability from failure analysis to requirements, mitigations, and validation plans
Designed for real-world physical AI systems with inspectable reasoning and source-linked expert review
Integrates with existing engineering stacks and workflows

Cons

May require initial setup of system context and evidence model to align with existing workflows
Dependent on the quality and completeness of input data sources for accurate analysis
Primarily focused on safety-critical industries, which may limit applicability to non-physical AI systems

Frequently asked questions about Saphira AI

What does Saphira AI do?

Saphira AI provides a unified validation platform for physical AI systems, integrating hazard analysis, safety requirements, simulated scenarios, and certification evidence into a single closed loop. It automates the generation of safety cases and evidence to streamline validation and accelerate certification.

Who is Saphira AI suitable for?

Saphira AI is designed for developers, engineers, and compliance teams working with AI-driven physical systems, particularly in industries like robotics, autonomous vehicles, and industrial automation where safety and compliance are critical.

How does Saphira AI integrate with existing workflows?

Saphira AI connects with the sources of truth already used by teams, such as designs, requirements, tests, and field data. It reuses the same system context as work expands, allowing different teams to begin with different problems while maintaining consistency.

What are the key features of Saphira AI?

Key features include failure and incident investigation, safety and security analysis, requirements and change impact management, validation and test planning, and a reusable AI system for expert engineering work with live assurance graphs.

Does Saphira AI support third-party validation?

Yes, Saphira AI is a member of the NVIDIA Halos AI Systems Inspection Lab, and its safety engineers review generated analyses before they reach an assessor, ensuring rigor in the validation process.

How do teams typically get started with Saphira AI?

Teams often begin by addressing the workflow blocking a program today, such as a hard decision or a specific safety or validation challenge. Saphira AI reuses the same system context as the work expands, allowing for incremental adoption.