DocSearch v4.5 introduces a new side-panel Ask AI experience available in standalone mode or triggered from search in hybrid mode, enabling richer assistance without leaving the page. This release also adds Agent Studio support, allowing DocSearch to use the same agent architecture as other Algolia products, and expands framework support with VitePress compatibility and upcoming Docusaurus adoption. Ask AI thread depth controls let customers set a maximum conversation depth, improving response accuracy and cost predictability for longer side-panel or full-page conversations. Click here to learn more.

The latest DocSearch release brings a more powerful, flexible, and conversational experience for both developers and end users. A redesigned Playground Editor offers live previews and deeper configuration control, while DocSearch v4.3 introduces Suggested Questions, a composable API, and improved UI/UX stability. Field Mapping now supports custom data shapes, expanding compatibility beyond crawler-generated content. With enhanced performance and new Ask AI–powered search on Algolia Docs, DocSearch delivers faster setup, richer customization, and smarter discovery. Click here to learn more.

Algolia SiteSearch UI Components introduce a flexible, open-source registry for creating AI-powered search interfaces faster. Built with shadcn on top of InstantSearch, these components simplify implementation across multiple use cases, including Ask AI. Developers and agents can easily customize layouts and interactions, even using generative tools like v0 or Cursor. SiteSearch accelerates development with production-ready UI patterns that reduce engineering effort and enable rapid, tailored search experiences. Click here to learn more.

Ask AI now delivers a more engaging and cost-effective experience. New Suggested Questions help users start conversations faster by surfacing curated, clickable prompts that instantly generate responses. Analytics Enhancements add token-level insights for deeper understanding of conversation flow. Token Efficiency improvements reduce costs by up to 50% while maintaining speed and accuracy. Expanded provider support, including OpenRouter, Anthropic, OpenAI, and Vercel AI SDK v5, ensures compatibility with the latest LLMs. Click here to learn more.

Algolia's Search Analytics now provide data insights at the Composition level. It tracks key metrics such as popular search queries, search volumes, click and conversions rates, or revenue for specific Compositions, all presented in intuitive dashboards that are easy to filter and consume.

Algolia MCP Server enables LLMs and Agents to securely access Algolia’s Search and Recommend APIs through the open Model Context Protocol (MCP). This managed, fully hosted service provides a universal gateway between AI systems and Algolia, simplifying integration and enhancing data-driven AI experiences. Click here to learn more and get started with the Algolia MCP Server. 

Ask AI is now generally available, expanding beyond documentation search to support broader site experiences - across support portals, blogs, marketing pages, and more. With new flexible UI options and streamlined setup, teams can quickly deploy accurate, conversational search powered by Algolia and the LLM of their choice. Click here to learn more.

Business users can now generate product collections using natural language prompts like “vintage dresses with a floral print.” Powered by NeuralSearch, this enhancement automatically curates relevant items based on semantic relevance. It reduces manual work, speeds up collection creation, and helps teams respond quickly to seasonal trends and merchandising needs. Click here to learn more. 

DRR Revenue reorders search results based on actual revenue contribution rather than clicks or conversions. This AI-driven ranking strategy allows businesses to surface high-value products and optimize for profitability without manual tuning. When activated, DRR Revenue works alongside Advanced DRR - enabling frequent updates and improved ranking precision for head queries. However, it is currently not designed to work in combination with Multi-Signal Ranking, as it only supports conversion-based optimization at this stage. Ideal for businesses with wide-ranging product prices, DRR Revenue helps shift focus from popularity to profitability, enabling more strategic, data-driven decisions that balance immediate performance with long-term growth. Click here to learn more.

Multi-Signal Ranking introduces an advanced approach to search result optimization by leveraging multiple data signals. This enhancement allows organizations to refine search relevance by incorporating diverse factors such as product attributes, business KPIs, and user interactions. By balancing multiple ranking signals beyond just popularity - businesses can improve relevance, drive higher conversions, and align search results with strategic objectives. This capability extends Dynamic Re-Ranking, ensuring more unique queries benefit from optimized ordering. Organizations can now prioritize factors like product margins, fast shipping, and brand affinity while maintaining search relevance. The intuitive admin interface allows easy configuration of ranking strategies, with continuous learning adapting to new data for sustained optimization. Click here to learn more.