AI APIs & LLM APIs
This cluster covers what changes when you build APIs backed by LLMs instead of conventional logic — from streaming and cost controls to RAG, embeddings, and vertical AI. Whether you're building your first LLM API or scaling an AI-powered product, these guides give you the architecture patterns and operational playbooks to do it right.
Articles
0 of 10 publishedBuilding LLM-Backed APIs: A Complete Guide
Everything you need to build, deploy, and operate production APIs powered by large language models.
AI API vs Traditional API
How LLM-backed APIs differ from conventional REST APIs in design, latency, cost profile, and reliability.
Cost Optimization for LLM APIs
Token caching, model routing, prompt compression, and other strategies to reduce LLM API spend at scale.
Open vs Proprietary LLM APIs
When to use OpenAI, Anthropic, or Gemini vs hosting your own open-weight model for cost and control.
OpenAI vs Anthropic vs Gemini
A developer-focused comparison of the three leading LLM API providers on capability, pricing, and reliability.
Streaming LLM API Responses
How to implement Server-Sent Events for LLM streaming, handle partial responses, and manage backpressure.
LLM Rate Limiting and Quota Management
How to manage token quotas, per-user limits, and cost caps for LLM APIs in production at scale.
RAG APIs: Architecture and Design
Building retrieval-augmented generation APIs: indexing, retrieval strategies, chunking, and reranking.
Embedding APIs: A Practical Guide
When and how to use embedding APIs for semantic search, clustering, and recommendation systems.
Vertical AI: Building Domain-Specific LLM APIs
How to build and differentiate LLM-powered APIs tuned for specific industries and use cases.
Expose and govern AI APIs with WSO2
WSO2 API Manager lets you publish, secure, rate-limit, and monetize LLM-backed APIs with usage controls and developer self-service.
The open, universal platform for managing every API and AI service at scale. 100% open source.