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Companies

Boldcharter

Deep learning systems that trade financial markets

Raised to date

$481K

of $481K offered across 1 Form D filing

Investors
6
Last filed
Apr 3, 2026

About

BoldCharter is a quantitative trading research company building deep learning systems that trade financial markets end to end. Its stated aim is to replace the hand-engineered feature pipelines of conventional algorithmic trading with models that learn directly from continuously evolving time series, so that intelligence generated no longer scales linearly with researcher headcount. The company positions this as the successor to the medium- and high-frequency algo trading built by firms like Renaissance, Millennium and Tower Research, and expects it to surface alphas that are machine-mineable but not human-identifiable. Founded in March 2025 by IIT Bombay alumni Mehul Goyal, formerly of AlphaGrep, and Nisheeth Lahoti, it is establishing a dedicated AI research and engineering lab.

Designs for regime change rather than backtest fit — the founders' argument is that most AI trading systems break because they are tuned ever more precisely to market environments that have already happened, so BoldCharter builds dynamic regime classification and end-to-end learned execution intended for conditions that have not occurred yet.

Funding

  • EquityFiled Apr 3, 2026Form D
    $481K/ $481K

Product

BoldCharter deep learning trading system

Quantitative trading system

An end-to-end machine-learned trading platform that ingests real-time market data to forecast price movement, executes trades algorithmically, and sizes positions dynamically from volatility forecasts, with no human-engineered features in the middle of the pipeline.

  • End-to-end deep learned trading with no human feature engineering
  • Models built for continuously evolving time series
  • Dynamic regime classification to detect fundamental changes in market conditions

Built for

Investors in the firm's trading strategies, alongside the quantitative researchers and engineers it is recruiting to build them

People on file