Ch
Chat2Report-Your AI Assistant for Financial Reports
Hacker NewsChat2Report-Your AI Assistant for Financial Reports
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, podcasting71%71% 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 HuntUnlikely to reach the leaderboard · Strong signals: user, email · Missing: mac, agents, macos49%49% 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, personal46%46% 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, intuitive46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released25%25% 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, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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