AI

AI News app to fight misinformation

Hacker News

AI News app to fight misinformation

The Problem: Social media platforms such as X, Facebook, and Reddit have become the primary news sources for most individuals. These platforms are designed to maximize engagement and provide information that reinforces existing biases. The mass adoption of these platforms has contributed to highly polarized societies and widespread misinformation and hate. Drooid’s Approach: Drooid tackles misinformation and bias by providing all sides of news stories. It gathers articles from various journalistic sources, processes them, and then generates short news summaries, around 60 words, which cover all sides, left, right, and center. Whenever possible, Drooid provides a short historical context with them. To give the complete picture faster, Drooid avoids overwhelming with excessive information. However, there is an In-depth news analysis feature to help you understand in detail "what exactly happened," "how different stakeholders are affected," "how they reacted," and "how various news reports contradict each other," and a lot more. On Drooid, you’re not just a passive reader; you can comment, share how you feel, and add context. Every comment appears in a community feed. You can read others' comments on news stories. With this, news becomes humane, not just facts and reports. For full transparency, every summary links back to the original articles. Making it easy to read and share original articles. It serves two purposes: readers get to know where the information is coming from, and publishers receive the traffic.

Share card

Actual performance

5points
2comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: maximize · Missing: supports, reddit linkedin, podcasting
88%88% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, context · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
36%36% 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, revenue
13%13% 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, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

AI
AI and News by AYLIEN26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI and News by AYLIEN

Hacker News8
AI
AI for News26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI for News

Hacker News1
NewsBang
NewsBang32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your First AI News & Insights APP

Product Hunt+239News
Ledes
Ledes48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI News Agent

Indie Hackers1ai
AI News
AI News26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI News and Analyses of AI Tools

Indie Hackers
AI News
AI News26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI News and Analyses of AI Tools

Indie Hackers
Ha
Hackobar – One feed for AI news42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hackobar – One feed for AI news

Hacker News5
AI NEWS HUB
AI NEWS HUB69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fully automated SaaS that scrapes,and publishes AI news.

Indie Hackers1ai
AI
AI News Analyst52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI News Analyst

Hacker News1
I
I built an app on top of Ethereum and IPFS to fight corruption58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built an app on top of Ethereum and IPFS to fight corruption

Hacker News3