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Writing on data you can trust, and AI on top of it.

Where does my data go?

2 min read

Trying to figure out if a new software tool is safe to use has become exhausting.

Most of us look for a quick answer to a simple question: “Where does my data go?”

But in the modern software landscape, that question is deceptively hard to answer. A tool might store your account safely in one region, but send your typed prompts to a completely different country or a third-party provider for processing. Both matter, and the rules are rarely clear on a company's website.

To cut through the confusion, I built a non-commercial side project around a simple 5-part checklist to evaluate how platforms handle privacy:

1. Storage vs. Processing: Tracking exactly where your data sits versus where it is actively computed.
2. Legal Jurisdiction: Knowing which country's privacy laws actually govern the company behind the tool.
3. Training Policies: Clear verification on whether your inputs are being used to train their systems.
4. Independent Certifications: Looking past marketing claims to find actual security stamps (like SOC2 or ISO).
5. Regulatory Fit: Checking if the tool's baseline matches strict industries like finance or healthcare.

The goal isn't to look for a definitive verdict. A framework like this is just a reliable starting point for protecting your data before you hit "Sign Up."

When you're trying out a new software or AI tool for your everyday work, what’s the number one thing that makes you hesitate to trust it?

www.trustkit.co 

(A visual breakdown of how these checks map out is in the image below)

Dartabase: a sourced public record of Nepali companies

2 min read

Nobody can tell you how many startups Nepal has. Dartabase is my weekend AI project to fix that: a free, public record of Nepali companies and new ventures, in Nepal and started by Nepalis abroad.

Diagram of how Dartabase turns sources into published facts in six stages: sources, collect, extract, check, store, review, with the rule that protects each stage

I kept wanting to look up who raised what, who registered, who listed, who quietly shut down, and there was no single place to check. The two most cited databases of Nepali companies do not even agree on how many exist. They are off by two orders of magnitude, and neither of them explains how it decides what counts.

So the one rule I set was that nothing goes in without a source. Every entry shows you the publication, the date and the link it came from. If two sources give different numbers, it shows you both instead of picking one. If only the month is known, it says only the month.

Darta (दर्ता) means registration in Nepali, so the name is really just that plus database.

I put it together over a weekend using AI, mostly so I could understand this space properly myself. AI made it a few days of work instead of a few months. Working out what actually counts as a source took a lot longer than the code did.

It is still very much a work in progress and I would rather be upfront about that. There are 37 events on it right now and around 1,100 companies, but only 32 of those have any real depth to them. The rest are thin registry stubs. Shark Tank Nepal season one is the first proper backfill with many more planned. Will plan to update dataset periodically.

If you know of a raise, a registration, a listing or a closure that should be on there, or you spot something that is wrong, please tell me.

And if you follow this space, I would like to know what would actually make it useful to you.

https://dartabase.org

A weekly Nepal newsletter and podcast

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