Adding AI to Laravel in 2026: The Complete Modern Guide (Laravel AI SDK, Prism, OpenAI, Claude & More)

Why add AI to your Laravel app in 2025?

AI is no longer a feature reserved for big tech. With modern Laravel packages and APIs, any developer can add intelligent features — text generation, chat assistants, document summarisation, lead scoring, and more — directly into their Laravel application in a matter of hours.

In this guide, we cover every modern approach available in 2025: the official Laravel AI SDK, the popular Prism PHP package, direct API calls to OpenAI and Anthropic, vector search for RAG, and AI-powered background jobs.

Method 1 — Laravel AI SDK (official)

The Laravel AI SDK is the official, Laravel-native way to work with AI providers. It gives you a unified, expressive API across nine providers including OpenAI, Anthropic, Google Gemini, Mistral, and Groq — all with zero boilerplate.

Installation

composer 

Basic text generation

use

Streaming responses

AI::text(

The SDK also supports structured output, tool calling, embeddings, image generation, and multi-turn conversations out of the box.

Method 2 — Prism PHP

Prism is a community-favourite Laravel package for building AI agents and chains. It is provider-agnostic and has excellent support for tool use, structured outputs, and multi-step agent loops.

composer 

use

Prism is ideal when you want fine-grained control over provider selection and agent behaviour per request.

Method 3 — Direct OpenAI API integration

For developers who want maximum control or are using OpenAI-specific features (like Assistants API or fine-tuning), direct integration via the openai-php/laravel package is a solid choice.

composer 

// config/openai.php — set OPENAI_API_KEY in .env

Method 4 — Anthropic Claude via HTTP client

Anthropic's Claude models (Sonnet, Opus, Haiku) excel at reasoning, coding, and long-context tasks. You can call them directly using Laravel's built-in HTTP client.

use

Method 5 — RAG with pgvector or Pinecone

Retrieval-Augmented Generation (RAG) lets your AI answer questions from your own data — documentation, CRM records, product catalogues — without hallucinating. The architecture is: embed your documents, store vectors, retrieve relevant chunks at query time, inject into the prompt.

Using pgvector with Laravel

composer 

// Migration

Method 6 — AI-powered background jobs

Long-running AI tasks (bulk document summarisation, nightly lead scoring) belong in queued jobs, not HTTP requests. Laravel queues make this trivial.

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Method 7 — Live AI chat with Livewire

Building a real-time AI chat interface inside your Laravel app is straightforward with Livewire 3 and streaming.

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Choosing the right approach

Here is a quick decision guide:

• Laravel AI SDK — best for greenfield Laravel apps. Official, clean API, multi-provider.
• Prism PHP — best for complex agents, tool-use chains, per-request provider switching.
• openai-php/laravel — best when you need OpenAI-specific features (Assistants, fine-tunes).
• HTTP client (Claude) — best for direct Anthropic integration without extra packages.
• pgvector + RAG — best when your AI needs to answer from your own data.
• Queued jobs — best for bulk or background AI processing.
• Livewire chat — best for building user-facing AI chat UIs inside your app.

Final thoughts

The Laravel ecosystem has matured enormously around AI. Whether you want a one-line text generation call or a full RAG pipeline with tool-calling agents, there is a clean, Laravel-native way to build it today.

If you are building an AI-powered SaaS or need a custom AI chatbot integrated into your Laravel application, I am available for freelance work.