About MoneySense.ai
Hello everyone, I'm Mayuresh, developer of MoneSense AI.
The Problem:
As an investor/analyst myself, I was spending 3-4 hours daily reading earnings reports, SEC filings, and financial articles—then manually extracting key insights, sentiment, and risks into spreadsheets. It was tedious, inconsistent, and time-consuming.
The Solution:
MoneSense AI is a Chrome extension that analyzes any financial page with one click. It instantly delivers:
📊 Sentiment scores (bullish/bearish/neutral)
📈 Key tickers and mentioned companies
🎯 Market drivers and catalysts
⚠️ Risks and opportunities
📝 Concise TL;DR summaries
📤 Clean JSON output for dashboards/models
What Makes It Different:
Works on ANY website (Any financial websites like Bloomberg, SEC.gov, Substack, etc.)
Consistent, structured output every time
No passwords - secure magic link authentication
Free to start,
Who It's For:
Individual investors researching stocks
Financial analysts building models
Traders scanning market news
Anyone who reads financial content regularly
What's Next:
Portfolio tracking integration
Email digest of analyzed content
Team collaboration features
API access for power users
I'd love to hear your feedback! What features would make this more useful for your workflow?
Try it free: https://moneysense.ai
I would say this is a very useful chrome extension, these kinda small tools really makes impact a lot and solves problems.
Thank you for your kind words.
Absolutely amazing product and also enjoyed while working on it. Need to get attention that this chrome extension deserves. Please go to our website and download it. Lets us know your feedback
Yes, thanks for this.
I just downloaded and amazed why it’s free, makes life so easy for traders and market researchers
We have kept if free because it does not cost us a lot. We want people to use and give us feedback so that we can work on it and make more market suitable product
Right. Power of AI should be available for everyone for excel their productivity
The problem framing here is spot on - reading financial content is one of those tasks that feels productive but the actual insight extraction rate is surprisingly low. Most of that 3-4 hours is cognitive overhead, not actual analysis.
A few thoughts on the roadmap: the JSON output feature is underrated. For power users who want to pipe this into their own models or dashboards, that's the kind of thing that creates sticky usage. Have you thought about letting users define custom extraction templates? Something like "always extract X, Y, Z for earnings reports" vs "extract A, B, C for news articles."
Also curious about accuracy calibration - how do you handle sentiment on nuanced content where the headline is bearish but the underlying data is actually positive? That disconnect trips up a lot of AI analysis tools.
Nice work identifying a real workflow pain point and building a focused solution around it.
thank you Rishi for your kind words. AI analyse the words from articles and gives you sentiments accordingly. I have set up a layer before actual LLM call to identify this which makes this product stand out with accuracy and sentiment analysis.
That pre-LLM layer is a smart architectural choice. A lot of sentiment tools trip on nuance because they let the LLM handle everything end-to-end without preprocessing context.
Curious about the implementation - are you doing keyword/phrase detection before the LLM call, or something more structural like identifying the document type first (earnings vs news vs analysis) and routing to different extraction logic?
The accuracy edge you're describing sounds like it could be a real differentiator, especially for users who've been burned by tools that confidently misread sarcasm or hedged language in financial writing.