Infrastructure for AI reasoning under strict data constraints.

Axiom enables cloud-grade AI reasoning on sensitive data without the data ever leaving its boundary.

We separate reasoning structure from data identity, allowing modern language models to operate on safe, identity-free representations while preserving semantic meaning.

Many high-value AI workflows are blocked today.

Not because models are weak, but because:

• sensitive data cannot move
• redaction destroys reasoning
• encryption blocks inference
• on-prem models cap quality and velocity

Axiom is built for environments where data movement is not allowed, but high-quality reasoning is still required.

Axiom introduces a semantic boundary:

• Sensitive data stays local
• Identity is removed deterministically
• Relationships, roles, and structure are preserved
• Only safe, structured reasoning context reaches the model

This makes cloud LLMs usable in regulated and high-trust environments without sacrificing reasoning quality.

• Correctness over hype
• Determinism over heuristics
• Explicit boundaries over implicit trust
• Auditable abstractions over opaque filtering

We treat failure modes as first-class concerns and design systems that fail safely.

Axiom is not a compliance tool.

It is infrastructure that allows intelligence to exist where data cannot move, unlocking AI reasoning in workflows that were previously off-limits.

Early-stage infrastructure project.
Focused on correctness, evaluation, and narrow real-world validation.

License will be determined as the project matures.

This repository is shared for transparency and early technical exploration.