Aligno
Indie HackersPinned design feedback. No client signup.
I built Aligno because client feedback on designs is the part of design work nobody enjoys. Email threads. Marked-up screenshots. The inevitable "jump on a call." Aligno gives designers one share link. Clients pin commen
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: email · Missing: mac, agents, macos59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · 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, personal40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting40%40% predicted probability of success on Indie Hackers, 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, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Feedbeggar63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Collecting client feedback has never been easier
Indie Hackers1b2bTr
Trab, Powerful client feedback tools49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Trab, Powerful client feedback tools
Hacker News4Ta
Taskify Design Feedback from Slack47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Taskify Design Feedback from Slack
Hacker News1Go
Golang Clarifai Client34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Golang Clarifai Client
Hacker News11F#
F# Kafka client57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
F# Kafka client
Hacker News4I
I couldn't find an impala client, so I made one41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I couldn't find an impala client, so I made one
Hacker News1A
A Dogecoin client in Ruby39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A Dogecoin client in Ruby
Hacker News1Ru
Ruby client for Sparkfun's Phant39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Ruby client for Sparkfun's Phant
Hacker News1El
Elasticsearch R client64%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Elasticsearch R client
Hacker News8Cl
Client side rsync lbirary41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Client side rsync lbirary
Hacker News2