The Gendai – AI Product Descriptions from CSVs

Hacker News

Hey Hacker News, Excited to share The Gendai (thegendai.com), a tool we've been working on to solve a pain point for e-commerce businesses: product descriptions. Manually writing unique and engaging descriptions for hundreds or thousands of products is a massive time sink. We built The Gendai to automate this process using AI. Here's how it works: Upload your CSV: If you're like many e-commerce folks, you manage product data in CSVs. The Gendai works directly with your existing CSV files. Our AI is trained to analyze product images or any detail within your CSV and generate descriptions. Instant, Unique Descriptions: In seconds, you get compelling, SEO-friendly product descriptions ready to boost your listings. We believe this CSV-first, image-powered approach is a game-changer for efficiency. No more tedious manual writing or complex API integrations just to get decent product descriptions. We're launching today and would love to get your feedback! Try it out at thegendai.com and let us know what you think in the comments. What features would be most useful for you? Any thoughts on the AI-generated descriptions? Thanks for checking it out!

Visit product View on Hacker NewsFeb 24, 2025

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

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos

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Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

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.

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.

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

33%33% 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

10%10% 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

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