lnt-sovereign 1.0.2

High-performance neuro-symbolic verification layer for AI validation and logic-based guardrails.

LNT: Logic Neutrality Tensor

Deterministic Validation Layer for AI-Generated Intents

⚖️ Overview (Proprietary Software)

LNT is a high-performance neuro-symbolic engine designed to enforce deterministic symbolic constraints on probabilistic AI outputs. It provides sub-millisecond scaling and formal Z3 consistency verification for mission-critical validation in FinTech, HealthTech, and automated infrastructure.

License Notice: LNT is proprietary software. This distribution contains the core engine and public example manifests. Industrial Rule Registries require a commercial license.

🚀 Key Technical Specifications

• Vectorized Kernel (BELM): SIMD-accelerated logic manifold ($O(n)$ complexity).
• Latency: 2.54 ms for 10,000 concurrent constraints (Intel i7 benchmark).
• Formal Security: SMT-based (Z3) manifest consistency verification.
• Audit Integrity: SHA-256 signature-chained decision ledger for regulatory compliance.

🛠️ Quick Start

Installation

pip install lnt-sovereign

Minimal Working Example

from lnt_sovereign.client import LNTClient

# Initialize the Validation Client (Toolbox Mode)
client = LNTClient()

# Define a structured proposal
proposal = {"funding": 15000, "context": {"age_days": 10}}

# Audit against a public logic manifest
result = client.audit(manifest_id="visa_application", proposal=proposal)

if result.status == "PASS":
    print(f"Validation Certified: Score {result.score}")
else:
    print(f"Policy Violations: {result.violations}")

📜 Technical Documentation

For detailed architecture, API reference, and the full whitepaper, visit the LNT Documentation Portal.

• Technical Whitepaper: Mathematical foundations and benchmark distributions.
• API Reference: Complete parameter registry and error codes.
• Integration Patterns: Deployment guidelines for high-concurrency systems.

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Maintained for high-reliability AI system development.