Cx

CxReports – Low-Code Tool for User-Facing PDF Reports

Hacker News

CxReports – Low-Code Tool for User-Facing PDF Reports

Marko here from Codaxy. For over two years, we have been working on CxReports, a low-code tool for creating user-facing PDF documents and reports. We first saw the problem in wealth management, where reports are crucial for the user experience. Software vendors have customers who ask for customized reports with unique content, branding, and visuals. The solution was to build a tool that allows customization for each customer, which even customers themselves can use. Over time, this evolved to be a generic solution that works for various other use cases. CxReports lets you build reports visually. You can connect to a database and get data using SQL queries. It supports scheduled report generation and delivery. The API enables accessing CxReports from other applications or workflows. https://cx-reports.com/ You can easily try it out with our Docker image - https://docs.cx-reports.com/getting-started/docker/ . We offer a free tier for registered users. How do you currently handle customized reporting? Are there specific challenges you face with generating user-facing reports? I’d love to hear your thoughts and feedback. Looking forward to the discussion!

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created
95%95% 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, dock, visual · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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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