AI SaaS Platforms
Multi-tenant Next.js apps with per-org prompts, billing, and SSO.
Next.js Development for AI-Native Products
Streaming chat, agentic copilots, RAG dashboards: we ship them on Next.js App Router because Server Components, Actions, and edge runtimes were practically designed for AI UX.
120+
Next.js AI apps shipped
<400ms
Median TTFB on edge
99.99%
Vercel deploy uptime
30 sec
Cold-start to first token
Why Next.js for AI MVPs
1
Streaming UX is the default
- Server Components stream HTML as LLM tokens arrive
- Suspense boundaries hide partial states elegantly
- useFormStatus / useOptimistic feel native for AI mutations
- AI SDK's useChat hook ships with the framework conventions
2
API keys stay on the server
- Server Actions hide OpenAI/Anthropic keys without an extra service
- Route handlers compose with middleware for tenant auth
- Edge runtime keeps secrets out of static bundles
- Vercel KV / Upstash for rate limits in 5 lines
3
Performance and cost
- ISR caches expensive AI summaries cheaply
- Edge runtime co-locates LLM calls with users
- Streaming reduces perceived latency to first byte
- Image optimization handles AI-generated thumbnails
4
Built-in SEO and AEO
- Metadata API for rich OG / Twitter cards
- JSON-LD via app/.well-known easy to inject
- Sitemap.ts and robots.ts ship with the framework
- RSC streams crawlable HTML, not blank shells
What we build with Next.js for AI
Full-stack AI apps with one codebase
Streaming Chat
App Router + AI SDK chat with persisted threads, markdown, and tool calls.
Agentic Workflows
Server Actions orchestrate tools, with progress streamed to the UI.
AI-Assisted Web Apps
Existing Next.js sites get inline copilots, search, and writing assistance.
Edge Inference Routes
Sub-100ms LLM endpoints deployed globally on Vercel Edge.
Pages Router Migration
Bring legacy Pages Router apps to App Router with streaming and Actions.
Next.js for AI: what we get right
RSC streaming, not waterfalls
We compose Server Components so AI tokens flow concurrently with user data, not sequentially.
Server Actions for LLM calls
No client-exposed API keys, no extra Express server: just typed mutations the UI awaits.
Edge or Node, never both
We pick the right runtime per route to balance cold start, memory, and cost.
ISR for AI outputs
Pre-compute LLM summaries once, serve cached, revalidate on data change: saves tokens and ms.
SEO-grade rendering
Crawlers see streamed HTML with citations and structured data, not JS shells.
Vercel-native, deploy-anywhere
Optimized for Vercel but tested on Cloudflare Pages, Netlify, AWS so you're not locked in.
Next.js for AI: what we get right
RSC streaming, not waterfalls
We compose Server Components so AI tokens flow concurrently with user data, not sequentially.
Server Actions for LLM calls
No client-exposed API keys, no extra Express server: just typed mutations the UI awaits.
Edge or Node, never both
We pick the right runtime per route to balance cold start, memory, and cost.
ISR for AI outputs
Pre-compute LLM summaries once, serve cached, revalidate on data change: saves tokens and ms.
SEO-grade rendering
Crawlers see streamed HTML with citations and structured data, not JS shells.
Vercel-native, deploy-anywhere
Optimized for Vercel but tested on Cloudflare Pages, Netlify, AWS so you're not locked in.
Next.js for AI products. FAQ
App Router. It was designed around streaming, which is exactly what AI UIs need. Pages Router still works but you give up Server Components, Server Actions, and the AI SDK's idiomatic patterns.
Not for most AI MVPs. Server Actions and route handlers cover LLM orchestration cleanly. We add a Python service only when you need heavy data pipelines, fine-tuning, or specialized vector workloads.
Edge for stateless inference fan-out (sub-100ms global TTFB). Node for routes that need fs, native modules, or long-running streams beyond 30 seconds. We mix per route.
Server Components stream crawlable HTML with citations and structured data. We use the Metadata API for OG/Twitter, sitemap.ts for indexing, and emit JSON-LD for FAQ and HowTo schema so AI search engines can cite the page.
Yes. We use React 18 concurrent rendering plus virtualized lists for traces, and stream agent steps as JSON over SSE. Even 100-step runs render at 60fps.
