**The most important numeric metric is `Amount in USD`, the reported funding amount per deal.** It is the only measure in this dataset, and the funding-size questions the data serves (ticket size by round, sector or city, and whether activity is speeding up or slowing) all rest on it. It is stored as text with Indian digit grouping (e.g. `3,90,00,00,000`), so it was parsed into a numeric USD value before ranking. **Highest records (largest deals)** - **Rapido Bike Taxi** (Series B, Bengaluru, 27/08/2019) is the largest at **$3.9 billion**. That is far above every other deal and looks like a possible data-entry error, so verify it before relying on it. - **Flipkart** (Private Equity, Bangalore, 11/08/2017) is next at **$2.5 billion**. - **Paytm** (18/05/2017) and **Flipkart** (21/03/2017), both Private Equity in Bangalore, are tied at **$1.4 billion** each. - **Paytm** (Funding Round, Noida, 25/11/2019) raised **$1.0 billion**. - The rest of the top 10 run from $700M (Flipkart.com, 2015) down to $585M (Udaan, Series D, 2019). - Most of the largest deals are Private Equity rounds, and most are in Bangalore. - Drums Food (21/07/2016) sorts to the top in some outputs, but its amount is missing (`nan`), so it is not a real top record. **Lowest records (smallest deals)** - The minimum reported amount is **$16,000**. Five startups share it: Hostel Dunia, Play your sport, Yo Grad, Enabli and CBS, all Seed Funding on 19/01/2015. - The next level is **$16,600**: Dealwithus, Leaf, Faaya, CleverSharks and InstaBounce, all Seed Funding on 02/02/2015. - None of the lowest records has a city or industry vertical. **Caveats** - Some deals have no amount, so they were excluded from the ranking. - The round type has inconsistent spellings, such as `Seed\nFunding` versus `Seed Funding`. - City names vary, for example Bangalore and Bengaluru. - Both the highest and lowest sides cluster in particular years and rounds, so check data quality before drawing benchmarks. The numbers come from the ranked highest/lowest queries I ran, which parsed `Amount in USD` into a numeric value. The rendered result blocks above show each ranking.