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Roundtable – Survey fraud and bot detection API

Hacker News

Roundtable – Survey fraud and bot detection API

Hi HN, we're Mayank and Matt of Roundtable ( https://www.roundtable.ai ). We launched our Survey Simulator as part of YC S23 (see Launch HN: https://news.ycombinator.com/item?id=36865625 ), and ultimately decided to pivot because we couldn't convince users to trust our results and our value proposition wasn't clear. We conducted tons of user discovery interviews, and a lot of big players talked about the pain of manual QC and bot detection. We launched a survey fraud and bot detection API (Alias; docs.roundtable.ai) that determines whether a bot is answering your survey or not. Our API embeds Javascript into survey programs (Forsta, Qualtrics, jsPsych, etc.) to track user behavior and make a judgment on whether the data is from a high-quality participant. You can use our demo, and try to break it, here: https://www.roundtable.ai/hn-demo . See if you can generate LLM-based text without any flags going off! Feedback welcome!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% 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: user, new · Missing: mac, agents, macos
56%56% 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
54%54% 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: users · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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