Logo
Deploy Now

SaaS Alternative

Perplexity Google Search You.com Bing Copilot

Categories

Self-Hosted Privacy AI LLM Research Search Engine Machine Learning Information Retrieval

Stars

35680

Forks

3918

Watchers

194

Developer links

Last Updated: 07-16-2026 01:21 PM (UTC)

Vane

Perplexity's search experience without Perplexity: Vane deploys Perplexica, an open-source AI answer engine built as the self-hosted alternative. Instead of returning a page of links, it reads your question, searches the live web through the SearxNG metasearch engine, and composes a direct answer with cited sources. Retrieval quality comes from embeddings and similarity search: fetched pages are re-ranked against the query so the model answers from the most relevant passages rather than whatever ranked first. Two query modes cover different needs - Normal mode runs a straightforward web search, while Copilot mode generates multiple reformulated queries and actively pulls content from top matches for harder questions. Focus modes specialize retrieval for academic papers, YouTube, Reddit discussions, Wolfram Alpha calculations, or the general web. The answering model is your choice: OpenAI-compatible APIs or fully local LLMs such as Llama 3 and Mixtral through Ollama, which keeps queries entirely on your infrastructure. Because SearxNG pulls live results, answers reflect current information, and no search history is tracked.

Vane
Vane

Benefits

  • Answers Without Surveillance
  • Hosted answer engines log every question you ask. Self-hosted Perplexica tracks no search history, and with a local LLM via Ollama, queries never leave your server.
  • Current Information, Not Stale Indexes
  • SearxNG pulls live results from many engines at query time and re-ranks them for relevance, so answers reflect what is on the web now rather than a cached crawl.
  • Relevance from Real Retrieval
  • Similarity search over embeddings selects the passages that actually address your question, cutting the padding and off-topic sources that plague raw web search.
  • Your Model, Your Cost Structure
  • Point it at an OpenAI-compatible API for maximum quality or run Llama 3 locally for zero per-query cost - the engine works the same either way.

Features

  • Cited Live-Web Answers
  • Questions are answered in prose with source links, composed from pages retrieved through SearxNG at query time.
  • Copilot Mode
  • Generates multiple reformulated queries per question and actively extracts content from top-matching pages for deeper research.
  • Focus Modes
  • Specialized retrieval for the general web, academic sources, YouTube, Reddit discussions, and Wolfram Alpha computations.
  • Embeddings and Re-Ranking
  • Similarity search scores retrieved passages against the query so the model answers from the most relevant material.
  • Local LLM Support
  • Run Llama 3, Mixtral, and other models through Ollama, or connect any OpenAI-compatible API endpoint.
  • SearxNG Metasearch Core
  • Aggregates many search engines without tracking, giving broad coverage and up-to-date results as the retrieval backbone.