Arro

Build better products using AI-powered research

63 followers

Build better products using AI-powered research

63 followers

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User research

Our AI Research Assistant augments product teams, using automated conversations to collect customer insights at scale.

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Launch tags:User Experience•Artificial Intelligence•UX Design

Launch Team

Render Sandboxes: a computer for every agentIsolated compute, persistent state and a real filesystem

Promoted

Website is nice. Having the interactive demos is super smart. I tried the FigJam one and it felt pretty natural. I liked how the chat interface is very open (whitespace) and conversational. I could see myself using this tool.

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2yr ago

AI Product Hunter

Congratulations on the launch! And Congratulations! Arro is evaluated as #1 of the day by AI Product Hunter(my product)! Judging from the "waitlist" and the badge on the HP, I guess this might be an accidental launch. Looking forward to try this someday.

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2yr ago

I stumbled on this through an ad and honestly, this AI thing sounds overhyped like do product teams really need another tool telling them what customers think, seems lazy to me, what happens if the AI gets it wrong?

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2yr ago

AI helping with product research sounds like it's cutting corners, real product insights come from human interaction, not automated chats, feels like you're prioritizing speed over genuine feedback, have you considered the quality of the AI conversations?

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2yr ago

Congrats on the launch! This AI Research Assistant sounds like a game changer for product teams looking to scale customer insights efficiently. Excited to see the traction it gains on PH! 🚀

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2yr ago

Elisi : AI-powered Goal Management App

Congrats on this impressive launch! The idea of using AI to gather customer insights at scale is a game changer for product teams. Can't wait to see how this improves user experience and drives traction. Upvoted!

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2yr ago

I think while an AI Research Assistant might sound impressive, it raises questions about whether automated conversations can really capture the nuance of customer insights, how do you ensure the AI isn't missing out on the subtle details that a human would catch, also curious about what kind of data is it being fed to make these judgments, isn't there a risk of biased outputs

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2yr ago

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