AI Governance

Responsible AI Policy

A.A. Litan LLC

Effective Date: March 7, 2026

Policy Owner: Founder & Chief Governance Officer

1Our Commitment to Responsible Intelligence

At A.A. Litan LLC, we believe that the power of advanced automation must be balanced with absolute clinical safety and ethical rigor. This policy governs the use of Large Language Models (LLMs) and automated decision-support systems across our flagship platforms: Cynoculist, Trade_Up, and DASTA.

Our approach is led by our founder, who holds industry-recognized certifications in the responsible, safe, ethical, and secure adoption of AI, ensuring that every line of code and every model deployment is filtered through a lens of high-integrity governance.

2The NIST AI RMF Framework Alignment

We do not deploy technology in a vacuum. Our internal risk management lifecycle is strictly mapped to the NIST AI Risk Management Framework (AI RMF).

Govern:

We maintain a culture of risk awareness where AI is never "black box" technology.

Map:

We proactively identify risks associated with third-party model dependencies.

Measure:

We conduct rigorous evaluations and "red-teaming" on third-party models, such as those provided by OpenAI, to test for hallucinations, prompt injections, and bias.

Manage:

We prioritize the safety of the end-user by ensuring AI outputs are assistive rather than autonomous.

3Data Privacy: The "Scrub-First" Mandate

The security of customer data is our primary differentiator. We have engineered a proprietary mechanism within Cynoculist, Trade_Up, and DASTA that acts as a secure gateway between our users and the LLM.

Mandatory De-identification:

Before any request reaches a third-party provider, our system automatically scrubs and de-identifies sensitive data, including PII, credentials, and proprietary technical strings.

Zero-Training Guarantee:

We utilize enterprise-grade API configurations ensuring that customer data is never used by third-party providers to train, retrain, or improve their models. Your data remains your own.

4Model Governance and Internal Approval

We maintain a strict boundary between public-facing tools and our internal infrastructure:

Third-Party Models (OpenAI):

Used strictly for processing de-identified technical summaries under our secure API protocols.

Internal Models (Google Gemini):

All internal model implementations are subject to a formal approval process. No internal model is deployed without an assessment of its safety parameters and alignment with our ethical standards.

5Human-in-the-Loop (HITL)

We believe in "Augmented Intelligence," not "Artificial Intelligence."

  • No critical security finding, "CyberScore," or executive risk narrative is delivered without a Human-in-the-Loop mechanism.

  • Our platforms are designed to provide decision-support, ensuring that a qualified professional always reviews and validates system-generated insights before they are finalized.

6Continuous Evaluation & Red-Teaming

The threat landscape for automated systems is constantly evolving. A.A. Litan LLC commits to:

Ongoing Red-Teaming:

We regularly stress-test our implementations against the OWASP Top 10 for Large Language Models.

Performance Evaluations:

We conduct periodic "evals" to ensure that the third-party models we consume continue to meet our high standards for accuracy and safety.

Ethical Audits:

We monitor for "model drift" and bias to ensure our outputs remain fair, objective, and helpful.

7Governance Oversight

This policy is a living document. As the regulatory environment changes, our founder's certified expertise ensures that A.A. Litan LLC remains at the forefront of safe and secure technology adoption.

We are committed to transparency and will continue to improve our processes to ensure we deploy technology safely, securely, ethically, and responsibly.

Inquiries regarding our AI Governance and Risk Assessment can be directed to:

Office of the Founder|info@cynoculist.com

This Responsible AI Policy was last updated on March 7, 2026