Get started with Algolia

Learn what Algolia is, how it works, and which path to follow to build your first search or AI experience.

What is Algolia?

Algolia is a hosted AI search and retrieval platform. Built API-first, it combines keyword, vector, and hybrid retrieval to power search, recommendations, retrieval-augmented generation, and AI agents. Algolia stores your data as JSON records that you query through the API, client libraries, and UI libraries.

How Algolia works

You send records from your data sources to an Algolia index. Index settings determine how Algolia matches, ranks, and filters those records. Your website, app, or AI agent queries the index and presents the response. Click and conversion events provide behavioral data for analytics and other features.

Use the Algolia dashboard to tune relevance, set up recommendations, create AI agents with Agent Studio, merchandise results, review analytics, and run A/B tests.

Choose a starting point

Build your first search experience

Build a working React search experience with sample data.

Build with AI agents

Use AI assistants and agents to build and maintain your Algolia integration.

Understand the basics

Learn how indices, records, attributes, and events work in Algolia.

Pick a library or integration

Find the API client, UI library, or platform integration for your stack.

Build your implementation

A basic search implementation has three parts:

1. Index your data as records.
2. Build a search UI that queries your index.
3. Tune relevance to improve matching, ranking, and filtering.

Once your data is in an index, you can work on the search UI and relevance in parallel.

Extend your implementation

Add other features when you need them:

• Send click and conversion events to collect analytics data and power features such as Personalization, Dynamic Re-Ranking, and most Recommend models.
• Add recommendations to suggest relevant items.
• Build a conversational experience with Agent Studio to ground AI responses in your index data.

Measure and optimize

Once your implementation is working, measure performance and test changes.

• Search analytics to see how users search and where they don’t find results.
• Recommend analytics to see how users interact with recommendations.
• Agent Studio analytics to see how users interact with your agents.
• A/B testing to compare index configurations before you roll them out.

Prepare to go live

Before you launch to production, secure your account and work through the checklist.

• Security best practices to restrict API keys and protect sensitive data.
• Implementation checklist to catch gaps before launch.