How to Integrate AI APIs into Your Web Projects
Published on 2/12/2026
Practical guide to adding AI capabilities to your web app—OpenAI, Anthropic, and open models via API.
Integrating AI APIs lets you add chat, completions, and embeddings to your web app. OpenAI's API and Anthropic's API offer powerful models; open-source options via Replicate and Together give more control. The Vercel AI SDK abstracts streaming, tool use, and provider differences. Postman's State of API 2024 shows 74% API-first adoption (up from 66%), 63% of teams ship APIs in under a week (vs 47% in 2022), and 62% of companies generate revenue from APIs. AI-driven API traffic grew 73% in 2024. This guide covers provider choice, security, and implementation patterns for 2026.
Choose your provider based on cost and features
OpenAI and Anthropic offer the most capable models. Google AI and Mistral are alternatives. Open-source models via Replicate, Together, or self-hosted Ollama reduce cost and latency for some workloads. Pick based on your needs: latency, context window, tool use, and pricing. Our AI tools collection lists Claude API and related resources.
Use SDKs and abstraction layers
The Vercel AI SDK provides a unified interface for chat, completions, and streaming across providers. LangChain and LlamaIndex offer orchestration for complex workflows. Start with the Vercel SDK for simple integrations; add LangChain if you need chains, agents, or retrieval. See AI tools for developers and future of AI workflow.
Secure your keys and handle errors
Never expose API keys in client-side code. Call AI APIs from serverless functions or your backend. Use environment variables and restrict key permissions. Implement retries, fallbacks, and clear error messages. Set token limits to control costs. Rate limits vary by provider—handle 429 responses gracefully. Reference our workflow automation guide for CI/CD integration.