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Draft for review. This is a baseline template, not legal advice. Have it reviewed by counsel before launch.

Legal

Security

We know you may bring sensitive research into KinetixAI, so we design the service to protect it. This page describes how we approach security. It describes our design intent, not a certification.

Last updated: October 2026

Your research stays yours

Papers, notes, and repositories you add to your Research RAG are stored in your workspace and used only to answer your questions. We do not use your uploaded content to train models, and we do not share it with other users.

Encryption

Traffic between your browser and KinetixAI is encrypted in transit using HTTPS. We protect stored data with access controls appropriate to its sensitivity.

Authentication and access

Accounts are protected by passwords that we store only as salted hashes, and you can sign in with Google. Access to production systems is limited to the people who need it. [Add multi-factor and SSO details as they ship.]

Safe retrieval

Our retrieval pipeline checks for prompt injection and poisoned documents so that answers stay grounded in your sources rather than following hidden instructions.

Reliability

We design for durability of your workspace data. We do not currently publish a formal uptime commitment outside a written service agreement.

Reporting a vulnerability

If you find a security issue, please email hello@kinetixai.ai with the details and steps to reproduce. We will acknowledge your report and work with you on a fix. Please give us reasonable time to respond before any public disclosure.

What we are working toward

We are building toward independent security reviews and formal certifications. We will state clearly which ones we hold once they are in place, and we will not claim a certification we have not earned.

Contact

Security questions: hello@kinetixai.ai.

Questions? Email hello@kinetixai.ai.

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KinetixAI
KXAI
Your KinetixAI research guide
Grounded in the papers below, never invented

I'm KXAI. Ask me about the papers in your bucket, their architecture, results or gaps, or ask me to map a paper of your own.

Map your own paper

Demo mode: answers come from the papers below. Mapping your own paper to 3D is a Scholar feature, coming soon. AI can make mistakes.