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I built a financial report assistant using Llamaindex
Hacker NewsI built a financial report assistant using Llamaindex
This is the first SaaS application I developed (based on RAG), which can quickly gain insights from tens of thousands of financial reports from thousands of companies. https://ch2report.com I am looking for 5 early users. If you would like to try this application, please send your registration email to my email (from my profile), and I would be happy to set up a free trial for you. I would love to hear all the feedback/suggestions. Thanks!
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting68%68% 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.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, email, using · Missing: mac, agents, macos57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: llama, io · Missing: https docs, excited, just released29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue14%14% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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