Confidential AI
Security Platform
A confidential platform for evaluating frontier AI model capabilities, adversarial behaviour, vulnerabilities, safety controls, and defensive use cases. Developed through a confidential collaboration with an external AI company, subject to written disclosure approval.
This page describes a product in confidential development. The collaboration partner, product name, internal system screenshots, evaluation results, acceptance communications, and specific technical details are not disclosed here.
Information on this page is limited to what can be discussed publicly without violating confidentiality obligations. The page will be updated if and when written disclosure approval is received from the collaboration partner.
If you have a legitimate interest in this platform — as a research institution, security organisation, or potential partner — please use the contact form at the bottom of this page to request a confidential discussion.
Frontier AI models require rigorous evaluation before deployment in high-stakes environments.
Frontier AI models — large language models and multimodal systems at the leading edge of capability — are being deployed in environments where their failure modes, adversarial vulnerabilities, and safety control gaps can have serious consequences. The tools and methodologies for evaluating these systems rigorously are still developing.
Key questions that are not yet well answered by existing evaluation frameworks include: how do frontier models behave under adversarial prompting designed to elicit harmful outputs? What are the boundaries of their safety controls and how consistently do those controls hold? How do models behave when given access to tools, code execution, or external data? What are the gaps between stated model capabilities and actual demonstrated performance?
Zentrix Labs is working on a platform to address these evaluation challenges in a structured, reproducible, and security-conscious way — developed through a collaboration with an external frontier AI company whose identity is withheld pending disclosure approval.
What the platform evaluates.
The following evaluation themes represent the public-facing scope of the platform. Specific methodologies, test suites, and results are not disclosed here.
Security research conducted responsibly.
All evaluation work conducted through this platform follows responsible disclosure principles. Vulnerabilities identified during evaluation are reported to the relevant AI company through agreed channels before any public disclosure. No evaluation results are published without the consent of the AI company whose systems are being evaluated.
We maintain a responsible disclosure policy for security research. If you have identified a security concern related to Zentrix Labs systems, please contact us at the address below. We commit to acknowledging receipt within 48 hours and to working in good faith toward resolution before any public disclosure.
Responsible disclosure contact: security@zentrixlabs.xyz
Request a confidential discussion.
If you represent a research institution, AI safety organisation, security company, or government body with a legitimate interest in AI evaluation capability — we are open to confidential discussions. Please do not submit classified or export-controlled information through this form.