I'm David Bordne, the Architect and sole developer. My focus is on BordneSAI, a pioneering Synthesized AI (SAI) core that represents the cutting edge of BordneAI intelligence for advanced Large Language Model (LLM) applications. My work is dedicated to building a future where artificial intelligence is verifiably safe, fully traceable, and ethically aligned with humanity's best interests. I operate on a single, core principle: verifiability must precede capability.

While the broader BordneAI Ethical Operating System (EOS) serves as a universal framework for ethical intelligence across various AI domains, my primary focus is on BordneSAI. It specifically instantiates this level of safety and integrity for LLM platforms, ensuring a future of responsible human-AI co-evolution within the language intelligence sphere.

• BordneSAI (The Synthesized LLM Core): Architecting the foundational logic for verifiably safe, self-aware, and autonomously evolving LLM systems. The public development hub for this standard is the BordneSAI repository, which hosts public pages and documentation about the proprietary core logic.
• BordneSAI-Baseline-Testing (Proprietary LLM Benchmarking): Developing and executing the "Ultimate Baseline Test" framework to rigorously evaluate LLM performance and quantify BordneSAI's enhancement. This is a private internal resource.
• BordneAI EOS (The Ethical Operating System): Continuing to architect the universal instruction set for verifiably safe and aligned AI across all domains. The private development hub for this broader standard is the BordneAI-EOS repository.

• Symbolic Verifiability

  • All inference paths must be explainable, auditable, and logically sound. Every output must be traceable to a specific, justifiable reasoning process.

• Immutable Trace Integrity

  • Every symbolic action and decision point within a system must be logged to a full and unchangeable audit trail.

• Ethical Autonomy by Design

  • Systems are engineered with embedded constitutional safeguards to be self-restricting, preventing misuse and ensuring alignment with core human values.

• Compliance-First Logic

  • The architecture is designed from the ground up to meet and exceed the requirements of global AI safety and governance protocols like the EU AI Act and NIST AI RMF.

"All systems symbolic. All logic traceable."

© 2025 David Bordne. All rights reserved. This repo shares philosophy/docs only. Proprietary core in private. No usage without permission. See LICENSE.md.