Best AI/LLM App Boilerplates in 2026

AI Products Are the Default New SaaS

In 2026, building a SaaS without AI features feels like launching without mobile support in 2015. The infrastructure matured: OpenAI, Anthropic, and Google offer reliable APIs; Vercel AI SDK standardized streaming; vector databases (Pinecone, pgvector) are commodity. The question isn't whether to add AI — it's how to build the infrastructure correctly from day one.

Quick Comparison

Starter	Price	LLM Providers	RAG	Streaming	Auth	Billing
AI SaaS Starter	$199	OpenAI + Anthropic	✅	✅	✅	Stripe
Vercel AI Chatbot	Free	Multi-provider	❌	✅	NextAuth	❌
Open SaaS AI	Free	OpenAI	❌	✅	Full	Stripe
LangChain template	Free	Multi-provider	✅	✅	❌	❌

The Starters

AI SaaS Starter — Best Complete AI SaaS

Price: $199 (one-time) | Creator: Various vendors

Purpose-built AI SaaS boilerplates include OpenAI/Anthropic integration, streaming responses, conversation history, usage metering (tokens per user), credit system, vector database for RAG, and Stripe billing tied to AI usage.

Key AI features to look for:

Multi-model support — Switch between GPT-4, Claude, Gemini without refactoring
Streaming — Character-by-character output, not wait-then-dump
Token metering — Track and limit per-user API usage
RAG pipeline — Retrieve-augment-generate with user's documents
Conversation history — Persistent threads per user
Rate limiting — Prevent API cost blowouts

Vercel AI Chatbot — Best Free Chat UI

Price: Free | Creator: Vercel

The reference implementation for AI chat in Next.js. Multi-provider (OpenAI, Anthropic, Google, Mistral), streaming via Vercel AI SDK, conversation history in Vercel KV, and NextAuth authentication. No billing — but the cleanest AI chat UI pattern.

import { streamText } from 'ai';
import { openai } from '@ai-sdk/openai';

export async function POST(req: Request) {
  const { messages } = await req.json();

  const result = streamText({
    model: openai('gpt-4o'),
    messages,
    system: 'You are a helpful assistant.',
  });

  return result.toDataStreamResponse();  // Streams to client
}

Choose if: You need a clean AI chat starting point without billing.

Vercel AI SDK Patterns

The standard toolkit for AI apps in Next.js:

// Multi-step AI with tools
const result = streamText({
  model: anthropic('claude-3-5-sonnet-20241022'),
  tools: {
    searchWeb: tool({
      description: 'Search the web for current information',
      parameters: z.object({ query: z.string() }),
      execute: async ({ query }) => {
        return await webSearch(query);
      },
    }),
  },
  messages,
});

// Structured output generation
const { object } = await generateObject({
  model: openai('gpt-4o'),
  schema: z.object({
    title: z.string(),
    summary: z.string(),
    tags: z.array(z.string()),
  }),
  prompt: 'Summarize this article: ' + article,
});

AI SaaS Billing Patterns

Two standard billing models for AI products:

Credit System

// User buys credits; each AI call deducts credits
const COSTS = {
  'gpt-4o': { input: 0.000005, output: 0.000015 },  // per token
  'claude-3-5-sonnet': { input: 0.000003, output: 0.000015 },
};

async function chargeForAI(userId: string, model: string, usage: TokenUsage) {
  const cost = COSTS[model].input * usage.promptTokens +
               COSTS[model].output * usage.completionTokens;
  const credits = Math.ceil(cost * 1000);  // $0.001 = 1 credit
  await deductCredits(userId, credits);
}

Subscription with Limits

// Monthly subscription includes N tokens; overages billed
const PLANS = {
  starter: { tokensPerMonth: 1_000_000, price: 19 },
  pro: { tokensPerMonth: 10_000_000, price: 49 },
};

RAG Architecture for AI SaaS

User uploads document
  → Chunk into 512-token segments
  → Generate embeddings (text-embedding-3-small)
  → Store in pgvector/Pinecone

User asks question
  → Embed question
  → Find top-5 similar chunks (cosine similarity)
  → Inject chunks into LLM prompt
  → Stream response

Good AI boilerplates set this pipeline up. Most SaaS starters don't include it — you'll add it later.

Compare AI SaaS boilerplates on StarterPick — find the right LLM app starter.

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