Deterministic AI Governance
We replaced probabilistic guardrails with cryptographic guarantees. Here's how Avarion ensures your AI coding agents are safe, auditable, and compliant.
Hermetic Generation
Standard agents read from a "live" file system, leading to race conditions and context contamination. Avarion agents operate in a Hermetic Container, accessing only a frozen, content-addressed snapshot of the context.
- Reproducible outputs from identical inputs
- No external network access during generation
- Deterministic behavior for audit trails
Merkle-Hashed Provenance
We treat your codebase like a blockchain. Every file, every dependency, and every work unit is hashed. A change in a low-level utility library ripples up the Merkle tree, invalidating all dependent features.
- SHA-256 cryptographic hashes
- Tamper-evident audit trails
- Automatic dependency invalidation
The "Zit" Lifecycle
Avarion enforces a strict state machine for every atomic unit of work (Zit). Each stage requires specific artifacts before progression is allowed.
Skipping stages is impossible. Each transition is cryptographically verified.
Memory Cortex
Traditional RAG is dumb. Avarion uses a Memory Cortex to store "Knowledge Atoms"—governed, versioned snippets of corporate wisdom.
- Vector-based semantic retrieval (Qdrant)
- Vetted patterns from human experts
- Prevents propagation of bad practices
AI Code Detection: 95.6% F1 Score
Our multi-signal detection engine combines five independent methods for maximum accuracy in identifying AI-generated code.
Fine-tuned Contrastive CodeBERT model trained on AI vs human code patterns. Highest accuracy signal.
Detects AI tool signatures, comments, and metadata left by Copilot, Claude, and Cursor.
Identifies structural patterns common in AI-generated code (naming, formatting, boilerplate).
Analyzes code generation speed and burst patterns that indicate AI assistance.
Examines commit patterns, author metadata, and change frequency for AI signatures.
Weighted ensemble aggregation produces a single confidence score for AI attribution.
95.6%
F1 Score
96.2%
Precision
95.0%
Recall
<2%
False Positive Rate
Agent Attribution
Not just "is this AI-generated?" but "which AI generated it?" We identify the specific coding assistant.
GitHub Copilot
Inline suggestions
Claude Code
Terminal agent
Cursor
AI-first IDE
Devin
Autonomous agent
+ support for additional agents including Windsurf, Tabnine, Amazon Q, and custom models
Want to dive deeper?
Read our comprehensive ML technical report or schedule a demo to see the technology in action.