Monday 2 November 2026Updated 08:13 IST
bharat.digital

India's digital economy, public infrastructure and security

Originals · Startup · Startups & Fintech

Tradl raises $4.1 Mn from Nexus and Stellaris to bring quant tools to retail traders

The Bengaluru startup pairs a language model with a rules based quant engine, so the same question on the same data always returns the same answer.

Tradl raises $4.1 Mn from Nexus and Stellaris to bring quant tools to retail traders
Cover: bharat.digital

Tradl, a Bengaluru AI trading platform, has raised $4.1 Mn (about Rs 40 Cr) in a seed round from Nexus Venture Partners and Stellaris Venture Partners, with a few angel investors also taking part. Inc42 first reported the round citing sources and said the company's filing with the Ministry of Corporate Affairs confirmed it. Tradl and its investors had not commented publicly at the time of reporting.

The product is built around a split between language and numbers. A user asks a question in plain language, the AI turns it into instructions for a quantitative engine, and that engine applies fixed rules to market data. Tradl says this means the same query on the same dataset always gives the same result, which it presents as a guard against the made up figures that general chatbots can produce.

The current toolkit includes an AI stock screener, technical charts and backtesting against historical data, plus sector rotation tracking and a calendar of corporate events. Chart pattern alerts, broader market insights and personalised option chains are listed as private access features. The website names NSE, BSE and MCX as exchange partners and CMOTS as its data partner.

Tradl was founded in 2025 by Shubham Bansal and Nilesh Raj, both IIT Guwahati graduates. Bansal spent about five years at Goldman Sachs and Raj worked at fintech startup Stable Money. The space is getting crowded: Trackk raised a $3.7 Mn seed round led by Lightspeed earlier this year, and StockGro has raised Rs 110 Cr as part of an ongoing Series B. If Tradl moves from analysis into trade execution, SEBI's framework for retail algorithmic trading would also come into play.

More originals