Deterministic foundation
Identical input produces identical canonical graph output and explainable diagnostics.
About Ontoly Cloud
Software intelligence that can show its work.
AI can generate code quickly. Engineering teams still need a deterministic layer that explains structure, impact, ownership, history, and release risk before that code ships.
The thesis
Models explain. Ontoly establishes the facts.
Repository truth should not change with prompt wording, model provider, or the size of a context window. Ontoly compiles software into a stable graph, then lets every product consume the same evidence.
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One semantic contract
CLI, cloud, editor, CI, MCP, and Agent Skills consume the same graph facts.
Evidence before explanation
Models receive compact evidence packs after Ontoly resolves the question.
Explicit uncertainty
Ambiguity, partial traversals, and unavailable history remain visible instead of becoming empty answers.
Our direction
A verification and intelligence layer for software teams.
Local first
The compiler and core graph remain useful without a hosted account or model provider.
Cloud when useful
Teams add collaboration, reports, history, policy, integrations, and managed agent access.
Open evidence
Every decision should link back to stable repository facts and clear provenance.
Start with evidence
Build with speed. Merge with evidence.
See how the Software Graph becomes Verify, Review, Explore, and repository intelligence.