We build AI features into Next.js applications using the Vercel AI SDK — streaming chat interfaces, tool calling, structured output generation, and multi-model support. From chatbots and AI copilots to content generation and data analysis tools, we leverage Vercel's AI SDK to ship production AI features fast.
Vercel AI SDK is a TypeScript toolkit for LLM apps: unified API across OpenAI/Anthropic/Google, streaming (text, tool calls, objects), React hooks (useChat, useCompletion), generative UI primitives. Any Node/edge runtime.
We build AI features into Next.js applications using the Vercel AI SDK — streaming chat interfaces, tool calling, structured output generation, and multi-model support. From chatbots and AI copilots to content generation and data analysis tools, we leverage Vercel's AI SDK to ship production AI features fast.
Key capabilities and advantages that make Vercel AI SDK Development the right choice for your project
Server-side streaming with the Vercel AI SDK's useChat and useCompletion hooks — delivering token-by-token responses for a responsive, ChatGPT-like user experience in your Next.js app.
Unified API across OpenAI, Anthropic, Google, Mistral, and more. Switch between models with a single line change — no rewriting integration code.
Let AI models call functions in your application — database queries, API calls, calculations, and actions — using the SDK's built-in tool calling support.
Generate type-safe structured data from LLMs using Zod schemas — extract entities, create forms, generate JSON, all with TypeScript type safety.
Discover how Vercel AI SDK Development can transform your business
Build ChatGPT-style interfaces in your Next.js app with streaming, conversation history, and tool calling — powered by any LLM provider.
Add AI copilot capabilities to your SaaS — inline suggestions, smart autocomplete, AI-powered search, and contextual help powered by your data.
Build AI content tools — blog writers, email generators, product descriptions, social posts — with streaming, templates, and multi-model support.
Real numbers that demonstrate the power of Vercel AI SDK Development
npm Downloads
Weekly npm downloads of the Vercel AI SDK
+100% YoY
Supported Providers
LLM providers supported out of the box
+5 annually
Framework Support
Next.js, Nuxt, SvelteKit, Remix, and more
Growing ecosystem
Our proven approach to delivering successful Vercel AI SDK Development projects
Define the AI features, choose the right models, and design the user experience for AI interactions in your application.
Integrate the Vercel AI SDK into your Next.js app with streaming routes, client hooks, and server actions.
Define tool functions, Zod schemas for structured output, and connect AI capabilities to your application's data and actions.
Deploy on Vercel with edge functions, monitor usage and costs, and iterate on prompts and model selection based on real user behavior.
Find answers to common questions about Vercel AI SDK Development
The Vercel AI SDK is a TypeScript library for building AI features in web applications. It provides React hooks (useChat, useCompletion), server-side streaming, tool calling, structured output, and a unified API across 15+ LLM providers — making it the fastest way to add AI to Next.js apps.
Let's discuss how we can help you achieve your goals
When each option wins, what it costs, and its biggest gotcha.
| Alternative | Best For | Cost Signal | Biggest Gotcha |
|---|---|---|---|
| LangChain.js | Complex chains, agents, retrievers in JS | Free OSS | Heavier abstraction; streaming DX less polished |
| Raw OpenAI/Anthropic SDKs | Full control, minimal dependencies | Free SDKs | You build streaming parsing, tool loops, retries yourself |
| Mastra | TypeScript agents with built-in workflows/memory | Free OSS | Newer ecosystem, smaller community |
| LlamaIndex.TS | RAG-focused TS apps, strong retrievers | Free OSS | RAG-heavy DX; overkill for plain chat UIs |
The SDK itself is free; true costs are LLM tokens + hosting. A streaming chat call (5K input + 1K output): GPT-4o ~$0.015, Claude Sonnet ~$0.03. At 100K chats/mo ~$1.5K-3K in model spend. Hosting on Vercel Edge: included in Pro ($20/mo + usage) up to first limits; AWS Lambda equivalent ~$50-200/mo. Switching providers (via SDK abstraction) saves 20-50% over time as cheaper models ship. Vs building streaming + tool-call parsing from scratch: SDK saves ~2-4 weeks engineering (~$15-30K) on typical projects.
Specific production failures that have tripped up real teams.
Mixing provider-specific streaming with useChat without protocol adapters breaks partial rendering—use toDataStreamResponse or match the UI message protocol.
Failed tool executions often just skip the tool result; always add server-side error paths and surface them to the UI.
Libraries using Node crypto/fs fail silently or at deploy; test on the same runtime you'll ship to.
Some versions buffer small chunks before flushing—pad SSE frames or use explicit flush to keep UX smooth.
v3 -> v4 -> v5 renamed core primitives; lock versions and plan 1-2 day migrations per major.
We say this out loud because lying to close a lead always backfires.
Python ecosystem (LangChain, LlamaIndex) is more mature; TS SDK matters most for Next.js frontends.
Vercel AI SDK focuses on client-server streaming; use LangGraph/Mastra for durable graphs.
The SDK's strength is streaming UX; for batch, direct provider SDKs are simpler.
Core APIs have evolved rapidly across v3-v5; expect breaking changes and migration work per major.