lnt-sovereign 1.0.5

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

LNT (Logic Neutrality Tool)

Sovereign Neuro-Symbolic Validation Layer

LNT is a production-grade neuro-symbolic validation framework designed to bridge the gap between probabilistic AI models and deterministic business logic. It provides a mathematically rigorous defense layer for AI agents, ensuring that every decision complies with strict, verifiable constraints before execution.

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Technical Concept

LNT operates on the premise that business rules are not just code—they are mathematical manifolds. By mapping natural language intent to vectorized logic constraints, LNT allows for high-performance, verifiable validation using SMT solvers (Z3) and optimized matrix operations (NumPy).

Core Features:

• Vectorized Logic Kernel: A highly optimized NumPy-based engine for sub-millisecond constraint evaluation.
• Formal Verification (Z3): Mathematical proof of manifest consistency, ensuring no conflicting rules exist in your policy.
• Sovereign SDK: A lightweight, typed Python client for seamless integration into MLOps pipelines.
• Fairness & Bias Auditing: Built-in statistical parity analysis to detect and mitigate bias in decision flows (AIDA/EU-AI Act ready).

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Project Status

• Audits: Internal Logic Verification Suite (Passing). All logic kernels are validated against formal proofs.
• Production Use: Valid. Deployed in high-throughput pipelines for financial and regulatory compliance validation.
• Benchmarks: Sub-millisecond latency verified for complex rule sets on standard commodity hardware.

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Quick Start

# Production install
pip install lnt-sovereign

Validator Example

from lnt_sovereign import LNTClient

# Initialize the production client
client = LNTClient(base_url="http://localhost:8000")

# Input proposal from an AI Agent
proposal = {
    "amount": 450.0,
    "user_risk_score": 15,
    "region": "US-EAST"
}

# Evaluate against the 'financial_compliance' manifest
result = client.audit("financial_compliance", proposal)

if result.status == "APPROVED":
    print(f"✅ Decision Authorized | Health Score: {result.score}")
else:
    print(f"❌ Blocked by Logic: {result.violations}")

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Documentation

• Architecture Overview
• Technical FAQ & Production Guide
• Roadmap & Evolution

LNT: Deterministic Trust for Probabilistic Intelligence.