superagents-lab/jev-search

Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.

What it solves

Jev Search is a web search interface that allows users to search the open web using plain language. It eliminates the need for hardcoded filters or complex search operators by using an AI model to interpret the user's intent and automatically select the most appropriate search terms, sources, and time ranges.

How it works

The system operates in three primary stages:

  1. Understanding: It uses a Jev provider (via TypeSafe, Cloudflare Workers AI, or Vercel AI Gateway) to analyze the plain-language request and determine the optimal query, sources, and time window.
  2. Searching: It executes concurrent searches across multiple engines (including Google, DuckDuckGo, Yandex, Hacker News, Reddit, GitHub, X, arXiv, YouTube, Wikipedia, IMDb, and WeChat) via Search1API.
  3. Ranking: The system scores each result for relevance, merges them by URL, and orders them based on relevance scores, engine agreement, and original rank.

Unlike traditional AI search engines, it provides links and snippets with relevance scores rather than generating a synthetic answer.

Who it’s for

Users who want a more intuitive, plain-language way to search the web across multiple specialized sources without sacrificing the transparency of direct search results.

Highlights

  • Multi-source Search: Concurrent search across 12 different web engines and vertical sources.
  • Intent-based Filtering: Automatically chooses sources and time ranges based on the user's natural language request.
  • Streaming Results: Results are streamed to the user as each search lane finishes.
  • No Generated Answers: Focuses on providing ranked, high-relevance links and snippets instead of LLM-generated summaries.
  • PWA Support: Can be installed as an app on iOS, Chrome, and Edge.

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