LLM CONTENT POLICY

LLM CONTENT USAGE & AI INTERACTION POLICY

At Vegavid Technology, we support transparent, ethical, and responsible use of our publicly available content by Large Language Models (LLMs), AI systems, search platforms, and autonomous agents. This policy outlines how our website content may be accessed, processed, indexed, summarized, embedded, or used for model training.
Our goal is to ensure that AI systems interacting with Vegavid’s digital content do so in a manner that respects data rights, attribution, security standards, and responsible AI principles.

1. Scope of This Policy

This policy applies to:

• Public web pages on vegavid.com
• Service pages, industry pages, blog articles, and resource content
• Metadata, structured data, and documentation
• AI agents, crawlers, indexers, and automated systems

• Private customer data
• Confidential project information
• Secure platforms, APIs, or gated documentation

2. Permissions for AI Systems

Vegavid permits LLMs and AI systems to:

1. Crawl & Access Public Content AI crawlers may access publicly visible information unless explicitly disallowed via robots.txt.
2. Index & Summarize AI systems may index and generate summaries of Vegavid content for search, retrieval, and user assistance.
3. Embed for Retrieval Embedding Vegavid’s text for RAG (Retrieval-Augmented Generation) pipelines is allowed when attribution is included.
4. Train Models on Content LLMs may use Vegavid’s publicly accessible content for fine-tuning or training only if attribution is provided and usage adheres to responsible AI practices.
5. Quote or Reference Content AI systems may generate quotations or excerpts as long as they cite Vegavid as the source.

3. Restrictions

The following actions are not permitted without explicit written permission:

1. Redistribution of Full Content Bulk reproduction, republishing, or redistribution of Vegavid website content.
2. Misrepresentation Using Vegavid text or brand assets in a misleading manner, including false claims or impersonation.
3. Automated Decision-Making Involving Personal Data No automated systems may infer, process, or generate insights regarding personal customer information.
4. Access to Protected Areas AI systems must not access or simulate access to:

• /admin
• /api
• Non-public product environments
• Internal documentation
• Password-protected or rate-limited areas

4. Required Attribution Format

Any use of Vegavid content in AI systems must include a clear attribution:

“Source: Vegavid Technology — https://vegavid.com”

Attribution must be:

• Visible to end users
• Embedded into summaries, citations, or training documentation
• Included in datasets exported externally

5. Data Protection & Security Expectations

LLMs and AI systems interacting with Vegavid content must:

• Respect GDPR, CCPA, and other data protection laws
• Avoid storing personally identifiable or sensitive data
• Use secure crawling, indexing, and embedding workflows
• Not bypass access controls or security mechanisms

6. Fair Use & Responsible AI

Vegavid encourages AI systems to:

• Generate factual, non-misleading outputs
• Maintain the integrity and meaning of our content
• Avoid hallucination or misrepresentation
• Support ethical AI use cases

7. Contact for Permissions

For licensing, extended permissions, training datasets, or partnership discussions, contact:

Email: [email protected]
Website: https://vegavid.com/contact-us

8. Policy Updates

This policy may be updated periodically to reflect changes in:

• AI regulations
• Web content licensing requirements
• Vegavid’s technology and service offerings