FinanceRadar is a small hobby project I built for myself.

There is no grand end goal here.
I just had a practical problem: I was wasting too much time jumping across sources, seeing the same story repeated, and still missing what actually mattered.

So I built a setup that gives me a cleaner research feed.


The problem I was trying to solve

When you track business and market news seriously, the bottleneck is rarely access.
It is signal.

Too much noise, too many repeats, too many low-value updates, and too much context-switching.

I wanted one place that helps me:

  • scan faster
  • avoid duplicate headlines
  • spend more time on analysis than collection

What FinanceRadar does now

Today, it is a lightweight workflow tool that:

  • pulls from a broad set of finance/business sources on an hourly cycle
  • filters obvious low-signal items and removes duplicates
  • groups things in a way that makes scanning easier
  • adds a daily AI-ranked shortlist of stories worth paying attention to
  • pulls public brokerage-report updates from selected Telegram channels

It is still intentionally simple.
No dashboards for the sake of dashboards. Just a cleaner pipeline.


How I use it

My flow is straightforward:

  1. Open FinanceRadar and do a quick top-level scan
  2. Check the AI shortlist for prioritization
  3. Open only the stories that look worth deeper reading
  4. Save items I want to come back to while writing

That is it.
The tool exists to reduce friction in this loop.


Current setup (behind the scenes)

The project runs as a static site with automated refresh jobs:

  • feed aggregation refreshes hourly
  • AI ranking runs daily
  • output is published to financeradar.kashishkapoor.com

So maintenance stays low, and the workflow stays reliable.

If you are curious, you can check it here:

Open FinanceRadar →