DEVELOPER RESOURCES
Build with a multi-model API. Evaluate the tradeoffs.
Guides for independent developers and small teams choosing a model gateway, controlling workload costs and testing useful AI features.
Platform and workflow guides
Start with the platform category, then explore routing, cost and task-specific evaluation. These guides distinguish suggested workflows from verified model behavior.
- AI API data privacy
- AI API for game dialogue
- AI API for indie developers
- AI API for prototyping
- AI developer console privacy
- AI gateway data handling
- AI gateway log retention
- AI model gateway
- API request workflow
- Chinese AI model API
- Hong Kong privacy compliance
- LLM API audit compliance
- LLM API cost estimation
- LLM API data routing
- LLM API for document processing
- LLM API privacy
- LLM model routing
- TokenBison payment processing
- affordable LLM API
- audit LLM API cost
- choose an AI gateway
- content generation API
- cryptographic proof of model identity
- geographic data processing
- integrate TokenBison API
- manage AI API costs
- monitor LLM API usage
- optimize AI application cost
- secure LLM API
- troubleshoot TokenBison API integration
- unified LLM API
- verify an AI gateway
Only published guides appear here. More candidates may still be under review.
Verified model integration examples
Supporting references for exact model IDs, minimal requests and observed pricing boundaries. A successful text request does not establish every optional API capability.
Choose a useful next step
Check the current model catalog and pricing, try a minimal request, or review trust information and limitations. Begin with public or non-sensitive sample data and evaluate outputs against your own acceptance criteria.