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Documentation Index

Fetch the complete documentation index at: https://docs.raily.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

Raily’s access control system provides fine-grained control over who can access your content, under what conditions, and with what permissions. Every access request is evaluated against your policies in real-time.

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How Access Works

When an AI system or application requests access to your content:
  1. Request is sent to Raily with content ID and requester information
  2. Access policies are evaluated based on rules and conditions
  3. Decision is made to allow or deny access
  4. If allowed, a signed URL and access token are provided
  5. Content is accessed using the provided credentials

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Access Policies

Define rules that control access to your content based on:
  • Requester identity - Who is requesting access
  • Purpose - How the content will be used (inference, training, RAG, etc.)
  • Time constraints - When access is allowed
  • License requirements - Required licenses or subscriptions
  • Rate limits - Maximum requests per time period

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Permissions

Control what actions are allowed when access is granted:
  • Full access to complete content
  • Preview or metadata only
  • Commercial use rights
  • Training or fine-tuning permissions
  • Redistribution rights

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Rate Limiting

Set limits on how frequently content can be accessed:
  • Requests per hour, day, or month
  • Burst allowances for temporary spikes
  • Per-requester or global limits

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Best Practices

Default Deny

Start with deny-by-default and explicitly allow access

Least Privilege

Grant minimum necessary permissions

Monitor Access

Regularly review access logs for unusual patterns

Test Policies

Test policies before deploying to production

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Next Steps

Authentication

Learn about authentication methods

Analytics

Track access patterns and usage