The semantic boundary for AI systems

Axiom Infra builds open-source infrastructure that enables cloud LLMs to reason over sensitive data by preserving semantic structure while keeping raw data strictly inside a trusted boundary.

It is designed from day one for high-quality reasoning, auditability, and compliance in regulated environments.

Axiom Infra enables AI systems to reason over sensitive data without that data ever leaving its trusted boundary.

As AI models become more capable, the real bottleneck is no longer intelligence — it’s how context is handled under compliance constraints.

Enterprises want to use cloud LLMs on real internal data, but compliance teams block it.
Axiom Infra makes that possible without exposing the data.

Modern AI adoption in regulated environments is blocked by a fundamental tradeoff:

• Cloud AI can’t access sensitive data due to compliance, residency, and audit constraints
• Redaction breaks reasoning quality by removing critical context
• Encryption preserves privacy but blocks utility — models can’t reason on ciphertext
• Compliance teams require proof, not promises, that data never crossed the boundary

Existing tools solve parts of this problem — none solve it end-to-end.

• Not an agency or services-first model
• Not blind redaction or masking of text
• Not encryption-only approaches that prevent inference-time reasoning
• Not a fully on-prem LLM stack

Axiom Infra is an infrastructure layer designed to enforce a semantic boundary:
raw data stays inside a trusted environment, while structured meaning remains usable for cloud-scale AI reasoning.

Most privacy tools protect data by reducing usefulness.
Axiom-Core protects data by changing how context is represented.

Axiom-Core SDK provides:

• Semantic abstraction — preserves structure and relationships while removing identity
• Deterministic transformation — repeatable, auditable, and policy-enforceable
• Explicit boundary enforcement — raw data is never allowed to exit
• Attested execution (preview) — verification for regulated workflows

The result is AI-usable context without data exposure.

Axiom-Core runs locally and transforms sensitive input into a safe, structured representation that cloud AI models can reason over — without ever seeing the raw data.

┌──────────────────────────────────────────────┐  
│                Raw Local Data                │  
└──────────────────────────────────────────────┘  
                     │  
                     ▼  
┌──────────────────────────────────────────────┐  
│             Semantic Abstraction             │  
└──────────────────────────────────────────────┘  
                     │  
                     ▼  
┌──────────────────────────────────────────────┐  
│               Identity Removal               │  
└──────────────────────────────────────────────┘  
                     │  
                     ▼  
┌──────────────────────────────────────────────┐  
│             Boundary Enforcement             │  
└──────────────────────────────────────────────┘  
                     │  
                     ▼  
┌──────────────────────────────────────────────┐  
│     Safe-to-Share Reasoning Context          │  
└──────────────────────────────────────────────┘  

• axiom-core — core SDK for semantic transformation and boundary enforcement
• axiom-core-docs — documentation, guides, and examples
• axiom-website — project website

Documentation: https://axiominfra.github.io/axiom-core-docs

Quick Demos: https://github.com/AxiomInfra/axiom-core-examples

Intelligence without boundaries is not trustworthy.
Axiom Infra defines the boundary.