For Enterprise
Auditable AI for Regulated Industries
Semantic verification provides full audit context for AI system behavior. Integrate with existing infrastructure via FFI bindings. No rewrite required.
The Challenge with Enterprise AI
AI systems increasingly drive critical business processes. But they operate as black boxes: difficult to audit, unpredictable in edge cases, and opaque when failures occur.
Regulatory requirements are expanding. Customers demand explainability. Your audit team needs evidence that AI behavior meets policy. Traditional logging captures what happened, not why it was correct.
AYIOS addresses this by building verification into execution, not adding it as an afterthought.
- Audit Gaps AI decisions lack the context auditors need to verify compliance
- Unpredictable Behavior Edge cases produce unexpected results with no clear explanation
- Integration Risk Adding verification to existing systems requires costly rewrites
- Vendor Lock-in Solutions tied to specific AI models limit flexibility
Semantic Verification at Runtime
AYIOS enforces semantic constraints during execution, detecting violations with full context.
Full Audit Context
When violations occur, AYIOS provides the complete semantic path to the failure: what constraint was violated, why it matters, and the chain of decisions that led there. Auditors get evidence, not logs.
Bidirectional Verification
Not one-way compilation. Complete round-trip from specification to execution and back. Trace any runtime state to its specification origin. Debug by inspecting intent, not implementation.
Model-Agnostic
AYIOS works with any capable AI agent. Swap models without rewriting verification logic. Your governance framework survives vendor changes and model updates.
Integrate Without Rewriting
FFI bindings for Python, TypeScript, and Rust. Add semantic verification to critical paths in your existing systems. The AI decides when to invoke formal methods.
Incremental adoption. Start with your highest-risk AI integrations. Expand coverage as you validate the approach. No big-bang migration required.
Boundary verification. Semantic integrity checks at FFI boundaries maintain guarantees when crossing into unverified code. Your existing systems don't need to understand AYIOS—they just receive verified outputs.
Enterprise Capabilities
Governance
Define semantic policies that AI systems must satisfy. Constraints are enforced at runtime, not checked after the fact.
Auditability
Complete semantic traces for every decision. Violations include the full path to failure with business-relevant context.
Integration
FFI bindings for Python, TypeScript, Rust. Add verification to existing systems without architectural changes.
Flexibility
Model-agnostic architecture. Your verification framework survives AI vendor changes and model updates.
Discuss Your Use Case
AYIOS is currently in development with enterprise preview available for qualified organizations.