Collie

Collie lets you embed an intelligent search bar into any website without building search from scratch. It uses AI to understand the intent behind user queries and returns relevant results by indexing your site content automatically, surfacing answers from pages, files, and data sources. This makes it a practical fit for documentation sites, knowledge bases, e-commerce stores, and content-heavy websites where visitors need to find information quickly without wading through complex menus. With a single JavaScript snippet, you can add search to any page, which is a key reason we think it's worth a look for developers and content managers alike. Under the hood, Collie works by crawling your website or syncing content via API, then using vector embeddings to enable semantic search. You get a customizable search UI that you can style with CSS/JS, plus the ability to set up filters and faceted search. The built-in analytics dashboard shows you what users are searching for, letting you fine-tune results over time. This is more than a basic site search plugin — it's a layer that learns from how your audience searches. The platform supports multiple content sources like PDFs, Notion docs, and GitHub repos, and integrates with static site generators such as Hugo and Jekyll. That means it slots into modern documentation workflows without a hard migration. Collie's free tier includes basic indexing, while paid plans unlock higher limits and advanced features like custom ranking and priority support. It's a hosted, cloud-based solution — you don't need to manage infrastructure. Compared to alternatives like Algolia, which is powerful but has a steeper learning curve and higher cost at scale, or Typesense, which requires self-hosting, Collie offers a middle ground: quick setup, semantic relevance, and no server to run. It's a solid option for teams that want to improve on-site search now, without building or operating a search stack themselves.