VisualEyes
Indie HackersYour professional A.I. design assistant
The first A.I design assistant that can predict the attention in your designs. The algorithm is powered by AI and neuroscience research on real eye tracking data from our platform and respective open datasets!
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: visual, open · Missing: mac, agents, macos67%67% 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.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto52%52% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
DeepShape54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
AI Graphic Design Assistant
Indie Hackerscommitment-full-timeCheckCheck49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Experienced and Professional Sneaker Verifications
Indie Hackers5clothingVilla Painting Auckland22%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Professional Villa Painting Auckland.
Indie Hackers
Adobe InDesign29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Design professional publications
AppSumo
Design Wizard52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Wonderful Wizard of Design is clicking its heels
AppSumo64Bo
Bootstrap for the design challenged58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Bootstrap for the design challenged
Hacker News2I
I Will Design You45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I Will Design You
Hacker News2My
My Newest Design: ZigZagLab47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
My Newest Design: ZigZagLab
Hacker News28De
Design Is For Everyone45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Design Is For Everyone
Hacker News2Fe
Fetchnotes re-design with Stylebot45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Fetchnotes re-design with Stylebot
Hacker News2