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Level up your n8n.io workflows with best-in-class web search. Here’s Khushi Shelat, our GTM Engineering lead, walking through Parallel’s n8n node and sharing some of the personal templates that help her stay organized using agentic web search.

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Parallel Web Systems

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Today, we’re launching the Parallel Search API, the most accurate web search for AI agents, built using our proprietary web index and retrieval infrastructure. Traditional search ranks URLs for humans to click. AI search needs something different: the right tokens in their context window. Parallel’s Search API is built from the ground up for AI agents, resulting in higher accuracy, lower costs, and lower latency for end-to-end agentic workflows.
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Today, we’re launching the Parallel Search API, the most accurate web search for AI agents, built using our proprietary web index and retrieval infrastructure. Traditional search ranks URLs for humans to click. AI search needs something different: the right tokens in their context window. Parallel’s Search API is built from the ground up for AI agents, resulting in higher accuracy, lower costs, and lower latency for end-to-end agentic workflows.

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Since our 1999 investment in Google, Kleiner Perkins has long partnered with teams building the web’s core infrastructure. Today, we are co-leading Parallel’s $100M Series A with Index Ventures. Founded by Parag Agrawal, Parallel Web Systems is building the web for agents. The platform provides a native search API and index that can retrieve, organize, and rank tokens—not blue links—so AI systems can access and reason over accurate, current context. As part of the round, Mamoon Hamid will join Parallel’s board. As Parag Agrawal puts it: “Agents aren’t issuing keywords. They declare intent and receive high-signal tokens.” Watch Mamoon’s conversation with Parag ⬇️

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Today we are announcing Keenable AI, an AI-native index of the best human knowledge we have, starting with the open web. AI seems to know just about everything until you ask it about something you know deeply. The answer isn’t wrong, but it's just very average. We started Keenable to fix this problem: every model and every agent should be able to query, reason over, and continuously learn from the living web. Backed by a $26M Seed from Accel and Conviction. Built by the team that took on Google at Yandex Search, with researchers and engineers from Amazon AGI, X, and Perplexity. The Web Search API and Web Query Language for AI are live now. Together they make the web queryable at AI scale. Both are free until end of September. Seven days of benchmarks, stories, and launches ahead. Let your agents search.

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