FileForge Finder: Local file search with AI-optimized export

Hacker News

Hope this sparks some conversation. Interested to get the community's take on an app we use internally to find files and provide targeted file content to chatbots. Biggest gains in search are for windows users but I am interested to get feedback from the spotlight users. With the AI export we originally used and MCP connector but when back to drag and drop export of file content due to security and universal applicability. No worries about your file security. Everything runs on-device and works offline. One click download at fileforge.com. Open to any feedback. Brent

Visit product View on Hacker NewsJul 27, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mcp, user, open · Missing: mac, agents, macos

77%77% 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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

15%15% 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 · Missing: web3, crypto, cryptocurrency

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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