Bid API Overview
The Affinity AI Bid API is a production-ready OpenRTB 2.6 compatible bidding service that enables intelligent, context-aware advertising. It serves as the central hub for programmatic advertising within the Affinity AI ecosystem, supporting both traditional display advertising and cutting-edge AI-native formats.
Service Information
Production Endpoint: https://bid-aura.affinity.net
Protocol: OpenRTB 2.6 with AdCP (Ad Context Protocol) extensions
Performance:
- p50 latency: < 50ms
- p95 latency: < 100ms
- p99 latency: < 200ms
- Throughput: 10,000+ requests/second
Core Capabilities
1. OpenRTB 2.6 Compatibility
Full support for the industry-standard OpenRTB 2.6 protocol, ensuring seamless integration with existing ad tech infrastructure:
- Standard bid request/response format
- Support for native formats
- IAB taxonomy integration
- Privacy compliance (GDPR, CCPA, GPP)
View OpenRTB integration guide →
2. AdCP Extensions
Optional extensions that enable advanced creative capabilities:
- Format-based creative assembly: Structured asset delivery with validation
- Universal macros: Standardized tracking that works across all publishers
- Custom format support: Framework for specialized ad formats
- Brand manifests: Standardized brand identity management
3. AI-Native Advertising
Support for contextual weaving formats that enable natural integration of brand messages into AI-generated content:
- Contextual weaving: Brand context woven into LLM responses
- AI search sponsored messages: Expandable sponsored content in search results
- Conversational AI ads: Natural brand mentions in chatbot conversations
4. Context Enhancement
Rich contextual signals for intelligent targeting without PII:
- Intent analysis: User intent classification with confidence scores
- Sentiment scoring: Emotional tone detection
- Funnel stage detection: User journey position tracking
- Topic extraction: Conversation topic identification
View context enhancement API →
Architecture
Request Flow
1. Publisher sends OpenRTB 2.6 bid request with optional Affinity AI
extensions 2. Bid API validates request and routes to appropriate backend
bidders 3. Backend bidders evaluate request and return bids with creative
manifests 4. Bid API aggregates responses and returns winning bid(s) 5.
Publisher renders creative and fires tracking pixels, including any
imptrackers URLs present in the native ad response
Supported Ad Formats
Traditional Formats
| Format | Description | Use Case |
|---|---|---|
| Native | Native ad units with structured assets | Content feed integration |
AI-Native Formats
| Format | Description | Use Case |
|---|---|---|
| Contextual Weaving | Brand context woven into LLM responses | Conversational AI platforms |
| AI Search Sponsored | Expandable sponsored messages in search | AI search monetization |
| Conversational Snippets | Natural brand mentions in chat | Chatbot advertising |
View complete format specifications →
Integration Options
Option 1: Standard OpenRTB Only
Use standard OpenRTB 2.6 without AdCP extensions:
Pros:
- Simple integration
- Industry-standard protocol
- Works with existing infrastructure
Cons:
- Limited creative capabilities
- No AI-native format support
- Basic tracking only
Option 2: OpenRTB + AdCP Extensions
Add AdCP support for enhanced capabilities:
Pros:
- Advanced creative assembly
- Universal macros
- AI-native format support
- Rich tracking capabilities
Cons:
- Slightly more complex integration
- Requires format definition queries
Option 3: Full Context Enhancement
Include rich contextual signals for optimal targeting:
Pros:
- Best targeting accuracy
- Higher CPMs
- Better user experience
- Privacy-compliant
Cons:
- Requires conversation analysis
- Additional processing overhead
Use Cases
1. AI Search Monetization
Goal: Generate revenue from AI search without disrupting user experience
Implementation:
- Extract intent and context from user queries
- Send bid requests with contextual signals
- Receive structured brand context
- LLM weaves sponsored mentions naturally
- Users can expand for detailed information
2. Homepage Tile Agent
Goal: Monetize browser homepage tiles with MCP-powered chat experiences
Implementation:
- Display sponsored brand tiles on new tab pages
- User clicks tile to trigger morphing animation
- Chat form auto-fills with agent name, welcome message, and MCP endpoint
- MCP server provides real-time product data and conversational AI
- Track impressions, clicks, and engagement
3. Conversational AI Advertising
Goal: Integrate brand mentions into chatbot conversations
Implementation:
- Analyze conversation for intent and sentiment
- Request contextual weaving format
- Receive brand context with weaving hints
- LLM incorporates brand naturally
- Track impressions when brand is mentioned
Privacy & Compliance
Privacy-First Design
The Bid API is designed with privacy as a core principle:
- No PII Required: Contextual targeting only, no personal identifiable information
- GDPR Compliant: Built-in consent management and privacy controls
- CCPA Compliant: US Privacy string support
- GPP Support: Global Privacy Platform integration
Contextual Signals Only
All targeting is based on contextual signals:
- User intent (what they're trying to accomplish)
- Conversation topics (what they're discussing)
- Sentiment (emotional tone)
- Funnel stage (journey position)
No user tracking, no cookies, no device IDs required.
Learn more about privacy compliance →
Getting Started
Quick Start Steps
1. Review the API contract - Understand request/response formats 2.
Choose integration method - Standard OpenRTB or with AdCP extensions 3.
Implement bid requests - Send properly formatted requests 4. Handle
responses - Parse and render creative content 5. Implement tracking -
Fire impression and click trackers, including imptrackers URLs from native ad
responses
Example Request
{
"id": "bid-request-123",
"imp": [
{
"id": "imp-1",
"native": {
"request": "{\"native\":{\"ver\":\"1.2\",\"assets\":[{\"id\":1,\"required\":1,\"title\":{\"len\":80}}]}}"
}
}
],
"site": {
"domain": "publisher.com",
"keywords": "family activities,outdoor adventures"
}
}
Example Response
{
"id": "bid-request-123",
"seatbid": [
{
"bid": [
{
"id": "bid-001",
"impid": "imp-1",
"price": 2.5,
"adm": "{\"native\":{\"ver\":\"1.2\",\"link\":{\"url\":\"https://example.com/product\"},\"assets\":[{\"id\":1,\"title\":{\"text\":\"Example Product\"}},{\"id\":2,\"img\":{\"url\":\"https://cdn.example.com/image.jpg\",\"w\":300,\"h\":250}},{\"id\":3,\"data\":{\"type\":3,\"value\":\"29.99 USD\"}}],\"imptrackers\":[\"https://tracking.example.com/pixel?id=abc123\"]}}"
}
]
}
]
}
Native ad responses may include an optional imptrackers array of impression
tracking URLs that must be fired via HTTP GET when the ad is rendered. See the
Response Format reference
for full details.
Next Steps
- Getting Started - Quick start guide
- OpenRTB Protocol - Complete endpoint documentation
- AdCP Extensions - Advanced creative capabilities
- Context Enhancement - Rich contextual signals
- Use Cases - Implementation examples
Support
Need help getting started?
- 📖 Documentation: Browse our comprehensive guides
- 💬 Technical Support: Contact our engineering team
- 🐛 Issues: Report bugs or request features
- 📧 Email: support@aura.tech
Ready to integrate? Head to the Getting Started Guide to begin.