Perplexica is an open-source AI search engine and answer engine that provides cited, conversational responses to user queries by searching the web in real-time. It serves as a self-hosted alternative to proprietary search platforms, utilizing advanced retrieval-augmented generation (RAG) workflows.

• Integrates the SearXNG metasearch engine to aggregate results from multiple search providers while maintaining user privacy and data sovereignty.
• Supports local and cloud-based Large Language Models (LLMs) including Ollama, OpenAI, Groq, and Anthropic for query synthesis and context processing.
• Features specialized search modes for Academic research, YouTube content discovery, and Wolfram Alpha computational queries.
• Utilizes a React-based frontend and Node.js backend to deliver streaming responses with verifiable source citations and image previews.

The system is deployable via Docker containers, ensuring environment consistency across local and server-side infrastructures. Perplexica is ideal for privacy-focused research, automated data retrieval, and self-hosted AI assistant integration.