Arlong Search AI
Innovating the Search for AI Agents and Humans
6 followers
Innovating the Search for AI Agents and Humans
6 followers
Arlong is a search engine for both AI agents and humans. For agents, it neutralizes prompt injections & provides structured links with threat analysis so your AI Agent Knows exactly which link to use instead of fetching all the pages in a link. For humans, it replaces raw link lists with AI Link Evaluations & cited overviews.
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Hey Product Hunt! 👋
I’m Ahilan, and along with Tuhin, we built Arlong AI.
A few years ago, when AI search was first blowing up, we actually built an early version of this. We shelved it, but about 7 months ago, we realized a huge gap in the market: no search engine is built specifically for AI agents.
Normally, when an AI agent scrapes a webpage, it extracts raw text blindly. This creates two massive problems:
Context Bloat: Webpage noise and DOM bloat eat up thousands of expensive tokens.
Security Risks: Scraped text can contain hidden indirect prompt injections that poison your agent or hijack its execution loop.
We built Arlong to fix the retrieval boundary: • Security: Sanitizes untrusted web data and neutralizes hidden prompt injections before they hit your model’s context. • Token Savings: Strips DOM bloat to cut downstream context token usage by up to 85%. • Pre-Click Evaluation: Scores link quality and safety pre-click so agents don't waste budget fetching low-signal pages.
It works out of the box with native MCP support for Cursor, ChatGPT, Codex, and custom API pipelines.
We are live in open beta today at arlong.org/ai! We’d love your feedback, thoughts, and questions. What features would you like to see next for your agent stack?