API to detect abusive content in 27 languages

Hacker News

Hello HN, I am Vadim of Tisane Labs ( http://tisane.ai ). We build text analytics APIs. My natural language processing journey started over a decade ago, when I built an NLP engine with an emphasis on scalability across languages. The engine served as a foundation of a startup I cofounded in 2010 ( https://en.wikipedia.org/wiki/LinguaSys ), which had Mark Cuban as an investor and was acquired in 2015. Utilizing our expertise, we're trying to tackle one of the most painful issues with the Internet today: abusive content. Hate speech, sexual harassment, cyberbullying are difficult to detect. Today's solutions mostly look for obscenities; correlation with training datasets only works with limited demos as the patterns of abuse are too many. Hate speech is more than just ethnic slurs. The API is a generic analytical engine, so it may be used for other purposes as well, but abusive content is our main focus. We'd love to hear your feedback, ideas, wishes, and complaints.

Visit product View on Hacker NewsSep 12, 2018

Share card

Actual performance

5points

4comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

87%87% 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: apis, plain · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

57%57% 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 · Missing: mobile apps, ios, personal

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

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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

An API To Detect Porn Content54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An API To Detect Porn Content

Hacker News3

#AlphanumericShellcoding, alphanumeric shellcodes on RISC-V [DEFCON'27]46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

#AlphanumericShellcoding, alphanumeric shellcodes on RISC-V [DEFCON'27]

Hacker News7

Franc – Detect natural languages55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Franc – Detect natural languages

Hacker News51

Full-featured Golang vendoring tool in 27 LOC55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Full-featured Golang vendoring tool in 27 LOC

Hacker News3

API to Detect Prompt Injection39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

API to Detect Prompt Injection

Hacker News2

Couvreur Vernon annuaire local68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Couvreur Vernon 27, couverture, zinguerie, isolation

Indie Hackers1$500/mob2c

Detect Adblock54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Detect Adblock

Hacker News6

Abusing RFC2616 section 8.1.4 to detect adblockers59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Abusing RFC2616 section 8.1.4 to detect adblockers

Hacker News7

Antimander – How to Detect Gerrymandering with Evolutionary Algorithms53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Antimander – How to Detect Gerrymandering with Evolutionary Algorithms

Hacker News2

Catchr – Secretly Detect Intrusions54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Catchr – Secretly Detect Intrusions

Hacker News2

Browse all products Analyze your launch