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Point Your AI Agent at api.tigzig.com and It Works Out Which Dataset It Needs. 38 Million Rows Across India and the US, Free.

Point Your AI Agent at api.tigzig.com and It Works Out Which Dataset It Needs. 38 Million Rows Across India and the US, Free.

Published: August 20, 2026

Tell your AI agent to go to api.tigzig.com and pull the full mutual fund NAV history since 2006, or India credit ratings, or US consumer delinquency, and it will work out which dataset it needs and download the file on its own. Close to 3.8 Cr (38M) rows across India and US, curated and updated daily. Free, no signup and no key.

Twenty years of mutual fund NAVs, around 330 macro, credit and valuation indicators, and seven separate filing datasets for Indian listed companies covering ratings, insider trades, pledges and takeovers.

Just ask your AI Agent:

go to api.tigzig.com and ....
download the full mf dataset for me
pull ratings and surveillance data for India
pull shiller index, US consumer delinquency and unemployment

There are three ways to use it.

For humans:

What sits on the macro side and the filings side

The macro side carries around 330 indicators across eight groups, US macro, US credit stress, US valuation, US insurance, India macro, global macro, markets and currencies, with each indicator carrying its own notes on annualisation and sign conventions, because those are the things that ruin a comparison without showing up as an error.

The India filings side is seven separate datasets: credit ratings, insider trading, promoter pledge, encumbrance, takeover and SAST filings, surveillance flags, and related party transactions. Each one downloads on its own or you can take all seven as a single SQLite file.

Every table has a downloads manifest with row counts and a generated_at stamp, so a script can check whether anything actually changed before pulling a file again.

Some practical notes from using this myself