AgentSea – private AI chat for sensitive work

Hacker News

Today we’re excited to introduce AgentSea, a private AI chat built for sensitive work. When you use closed-source AI models, your data can: – be stored – pulled into training pipelines – shared with third parties That might be fine if you’re making memes or drafting LinkedIn posts. But it becomes a serious risk when you’re pasting contracts, health info, financial data, or business secrets. That’s why we built AgentSea. In Secure Mode, all chats run on open-source models or models hosted on our own servers. Your data never leaves, is never used for training, and is never leaked. Agentsea also gives you access to 100s of community-built agents, along with tools like Reddit, X, and YouTube search. Try it here: agentsea.com Would love feedback from the HN community.

Visit product View on Hacker NewsSep 19, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, pipe, io · Missing: https docs, just released, exist

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue

26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, introduce · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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