Digital Scents – A smart diffuser and scent streaming service

Hacker News

Hi HN, We’re building Digital Scents, the world’s first scent streaming platform with a smart diffuser and a universal scent format (USF). Just as music and video became digital and streamable, we believe scent is the next sensory frontier. Users can stream, personalize, and even create scents using our mobile app and proprietary diffuser. The system is powered by a standardized digital scent format that enables scent to be distributed, shared, and monetized globally. What sets this apart: - Smart diffuser that reproduces over 10,000 scent profiles via app - Creators can sell scent compositions using a "creator mode" - Partnerships with luxury hotels, salons, game studios, and wellness brands - Patent-pending Web3/NFT tech to authenticate scent IP - Selected by JETRO for the J-StarX Silicon Valley program We’re exploring applications across wellness, hospitality, gaming, and entertainment—and open to feedback, collaborations, or investment conversations. Website: https://www.digital-scents.com Would love to hear your thoughts on how scent can become part of the digital experience.

Visit product View on Hacker NewsJun 19, 2025

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

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

62%62% 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, 000, io · Missing: https docs, excited, just released

47%47% 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 · Strong signals: ios, personal, video · Missing: mobile apps, entrepreneurs, apps

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, using, open · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

9%9% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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