About

Why it exists

If you search for a cafe in Nagpur you get listings and star ratings. Neither answers the question people actually have, which is usually specific: can I work here for four hours, is there a socket I can reach, is it still open at eleven, what will two of us spend.

Those facts exist in public — scattered across each cafe's own site, its social accounts and its listings. Nobody had put them in one table. That is the whole idea.

Who runs it

Ajinkya Pisal — engineering lead by trade, building software for a living and this on the side. Not a food writer, which is the honest framing for what this is. The interesting problem was never whether a flat white is good; it was whether an accurate, current local guide can be compiled from public data and kept honest without anyone driving around Nagpur with a notebook.

It started as the question you ask before working somewhere for three hours: is there a socket I can actually reach, is it quiet enough to take a call, is it still open at eleven, what will two of us spend. Nobody publishes that. Zomato tells you a place exists and what it costs. Nothing tells you whether you can get anything done there.

So this is an engineering answer to a mundane problem. The whole thing is a pipeline: it reads 139 cafes from open data and the Places API, computes every score from published weights, and re-checks itself on a schedule. The build refuses to publish a page that reads as templated, says too little to be worth reading, or rests on a fact older than 90 days — those are tests, not intentions.

Which means the method matters more than my opinion, so the method is what gets published: the scoring weights, the source list on every cafe page, and the full dataset under an open licence. If a ranking here looks wrong, check the arithmetic rather than taking my word for it. I would much rather be correctable than authoritative — and if you have actually been somewhere on this list, the report form on its page beats anything I can compile from a desk.

Reach me at [email protected], or through the contact page.

How the data is gathered

Honestly, and with a limitation stated up front: we have not visited these cafes. Every attribute is compiled from public sources, and each one is cited on the cafe's own page with a link to the record it came from. Where sources say nothing, we record nothing rather than guessing.

Rankings are computed from that data using weights published on how we rank — no editorial thumb on the scale. The full dataset is openly licensed.

How it pays for itself

Advertising, and nothing else. We take no payment from cafes, accept no sponsored placements, and no cafe can buy a position in a ranking — the order is computed, so there is nothing to sell. Ad slots are marked as advertisements.