Core Concepts

Overview

Raily is built around four core concepts that work together to give you complete control over your content in the AI era:

Content

Your articles, documents, images, and other digital assets

Policies

Rules that control who can access your content and how

Access Requests

When AI systems request permission to use your content

Analytics

Insights into how your content is being used

Content

Content is the foundation of Raily. It represents any digital asset you want to protect and monetize.

Content Structure

Every piece of content in Raily has:

Field	Description	Example
`id`	Unique Raily identifier	`cnt_abc123xyz`
`externalId`	Your internal identifier	`article-456`
`title`	Human-readable name	”Q4 Market Report”
`type`	Content category	`article`, `report`, `image`
`source`	Original location	`https://example.com/...`
`metadata`	Custom attributes	Author, date, tags
`policyId`	Applied access policy	`pol_xyz789`

Content Types

Raily supports various content types, each optimized for different use cases:

Articles & Blog Posts

Text-based content like news articles, blog posts, and editorial content.

const article = await raily.content.create({
  type: "article",
  title: "Breaking: AI Regulation Update",
  source: "https://news.example.com/ai-regulation",
  metadata: {
    author: "John Doe",
    section: "Technology",
    publishedAt: "2024-01-20T10:00:00Z"
  }
});

Research & Reports

Long-form documents like research papers, whitepapers, and industry reports.

const report = await raily.content.create({
  type: "report",
  title: "2024 AI Industry Analysis",
  source: "https://research.example.com/ai-2024.pdf",
  metadata: {
    pages: 150,
    price: 499,
    category: "Premium Research"
  }
});

Images & Media

Visual content including photos, illustrations, and graphics.

const image = await raily.content.create({
  type: "image",
  title: "Product Photography - Series A",
  source: "https://cdn.example.com/photos/product-a.jpg",
  metadata: {
    resolution: "4000x3000",
    license: "commercial",
    photographer: "Jane Smith"
  }
});

Datasets

Structured data collections for AI training and analysis.

const dataset = await raily.content.create({
  type: "dataset",
  title: "Customer Sentiment Analysis Dataset",
  source: "s3://datasets/sentiment-v2.parquet",
  metadata: {
    records: 1000000,
    features: ["text", "sentiment", "confidence"],
    version: "2.0"
  }
});

Content Lifecycle

Create

Active

Content is available for access requests and policy enforcement

Policies

Policies are the rules that govern how AI systems can access your content. They’re powerful, flexible, and designed for complex real-world scenarios.

Policy Structure

{
  id: "pol_xyz789",
  name: "Enterprise Access Policy",
  description: "Controls access for enterprise AI partners",
  rules: [
    {
      action: "allow",
      priority: 1,
      conditions: { /* when this rule applies */ },
      permissions: [ /* what the requester can do */ ],
      rateLimit: { /* usage limits */ }
    },
    // ... more rules
  ],
  defaultAction: "deny"
}

Rule Evaluation

Rules are evaluated in priority order. The first matching rule determines the outcome.

Conditions

Conditions determine when a rule applies:

Identity
License
Usage
Time

conditions: {
  requesterId: ["partner_openai", "partner_anthropic"],
  requesterType: "ai_provider"
}

conditions: {
  hasValidLicense: true,
  licenseType: ["enterprise", "professional"],
  licenseExpiry: { after: "now" }
}

conditions: {
  purpose: ["training", "inference"],
  commercialUse: false
}

conditions: {
  time: {
    after: "2024-01-01",
    before: "2024-12-31",
    daysOfWeek: ["monday", "friday"]
  }
}

Permissions

Permissions define what actions are allowed:

Permission	Description
`full_access`	Complete content access
`preview_only`	Limited preview (first 500 chars)
`metadata_only`	Access to metadata, not content
`commercial_use`	Can use in commercial applications
`training`	Can use for AI model training
`inference`	Can use for AI inference only

Rate Limiting

Control usage volume to prevent abuse and manage costs:

rateLimit: {
  requests: 1000,      // Maximum requests
  period: "hour",      // Time window: minute, hour, day, month
  burst: 100,          // Allow short bursts above limit
  scope: "requester"   // Apply per requester or globally
}

Policy Example: Tiered Access

const tieredPolicy = await raily.policies.create({
  name: "Tiered Content Access",
  rules: [
    // Enterprise: Full access, high limits
    {
      action: "allow",
      priority: 1,
      conditions: { licenseType: "enterprise" },
      permissions: ["full_access", "commercial_use", "training"],
      rateLimit: { requests: 10000, period: "hour" }
    },
    // Professional: Full access, moderate limits
    {
      action: "allow",
      priority: 2,
      conditions: { licenseType: "professional" },
      permissions: ["full_access", "commercial_use"],
      rateLimit: { requests: 1000, period: "hour" }
    },
    // Basic: Preview only, low limits
    {
      action: "allow",
      priority: 3,
      conditions: { licenseType: "basic" },
      permissions: ["preview_only"],
      rateLimit: { requests: 100, period: "day" }
    },
    // Default: Deny all others
    {
      action: "deny",
      priority: 99,
      conditions: { default: true },
      message: "Please obtain a license to access this content"
    }
  ]
});

Access Requests

When an AI system wants to use your content, it sends an access request. Raily evaluates the request against your policies and returns a decision.

Request Flow

Request Structure

const request = await raily.access.check({
  contentId: "cnt_abc123",
  requesterId: "partner_openai",
  context: {
    purpose: "inference",
    model: "gpt-4",
    userAgent: "OpenAI-API/1.0",
    ipAddress: "192.168.1.1"
  }
});

Response Types

Granted
Denied

{
  allowed: true,
  contentUrl: "https://cdn.raily.ai/...",
  token: "ey...",
  expiresAt: "2024-01-20T11:00:00Z",
  permissions: ["full_access", "inference"],
  rateLimit: {
    remaining: 999,
    resetAt: "2024-01-20T11:00:00Z"
  }
}

{
  allowed: false,
  reason: "rate_limit_exceeded",
  message: "Hourly request limit reached",
  retryAfter: "2024-01-20T11:00:00Z"
}

Analytics

Raily provides comprehensive analytics to help you understand how your content is being used and optimize your monetization strategy.

Key Metrics

Request Volume

Total access requests, broken down by granted vs denied

Top Requesters

Which AI systems are requesting your content most

Revenue

Earnings from licensed access

Usage Analytics

const usage = await raily.analytics.usage({
  period: "30d",
  groupBy: "day"
});

// Returns:
{
  totalRequests: 45230,
  allowed: 42100,
  denied: 3130,
  uniqueRequesters: 15,
  byDay: [
    { date: "2024-01-01", requests: 1520, allowed: 1480, denied: 40 },
    { date: "2024-01-02", requests: 1610, allowed: 1550, denied: 60 },
    // ...
  ],
  topContent: [
    { id: "cnt_abc", title: "AI Report 2024", requests: 8500 },
    { id: "cnt_def", title: "Market Analysis", requests: 6200 }
  ],
  topRequesters: [
    { id: "partner_openai", requests: 25000 },
    { id: "partner_anthropic", requests: 12000 }
  ]
}

Revenue Analytics

const revenue = await raily.analytics.revenue({
  period: "30d",
  currency: "USD"
});

// Returns:
{
  totalRevenue: 15420.00,
  byLicenseType: {
    enterprise: 12000.00,
    professional: 3000.00,
    basic: 420.00
  },
  byContent: [
    { id: "cnt_abc", title: "AI Report 2024", revenue: 8500.00 },
    { id: "cnt_def", title: "Market Analysis", revenue: 4200.00 }
  ],
  growth: {
    vsLastPeriod: 0.15,  // 15% increase
    trend: "up"
  }
}

Putting It All Together

Here’s how these concepts work together in a real-world scenario:

Publisher Registers Content

A news publisher adds their premium articles to Raily

Publisher Creates Policy

They set up a policy allowing licensed AI partners to access content

AI System Requests Access

An AI company wants to use the articles for their chatbot

Raily Evaluates Request

Raily checks if the AI company has a valid license

Access Granted

If licensed, Raily provides secure access to the content

Analytics Recorded

Every access is logged for reporting and billing

Publisher Gets Paid

Based on usage, the publisher receives revenue

Next Steps

Content Ingestion

Learn how to import your content at scale

Policy Templates

Start with pre-built policies for common scenarios

Analytics Deep Dive

Get the most from your analytics data

API Reference

Explore the complete API documentation

Getting Started

Content Management

Integrations

Use Cases

Core Concepts

Overview

Content

Policies

Access Requests

Analytics

Content

Content Structure

Content Types

Content Lifecycle

Policies

Policy Structure

Rule Evaluation

Conditions

Permissions

Rate Limiting

Policy Example: Tiered Access

Access Requests

Request Flow

Request Structure

Response Types

Analytics

Key Metrics

Request Volume

Top Requesters

Popular Content

Revenue

Usage Analytics

Revenue Analytics

Putting It All Together

Next Steps

Content Ingestion

Policy Templates

Analytics Deep Dive

API Reference

Getting Started

Content Management

Integrations

Use Cases

​Overview

Content

Policies

Access Requests

Analytics

​Content

​Content Structure

​Content Types

​Content Lifecycle

​Policies

​Policy Structure

​Rule Evaluation

​Conditions

​Permissions

​Rate Limiting

​Policy Example: Tiered Access

​Access Requests

​Request Flow

​Request Structure

​Response Types

​Analytics

​Key Metrics

Request Volume

Top Requesters

Popular Content

Revenue

​Usage Analytics

​Revenue Analytics

​Putting It All Together

​Next Steps

Content Ingestion

Policy Templates

Analytics Deep Dive

API Reference

Overview

Content

Content Structure

Content Types

Content Lifecycle

Policies

Policy Structure

Rule Evaluation

Conditions

Permissions

Rate Limiting

Policy Example: Tiered Access

Access Requests

Request Flow

Request Structure

Response Types

Analytics

Key Metrics

Usage Analytics

Revenue Analytics

Putting It All Together

Next Steps