The startup offers a machine learning platform that forecasts commodity prices by analyzing geopolitical news, market fundamentals, and price actions through artificial intelligence. This technology enables commodity traders and analysts to manage economic risks associated with price volatility, delivering consistent returns regardless of market fluctuations.
Funding
$10.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Commodity markets are increasingly volatile due to geopolitical events and the transition to sustainable energy, making reliable price forecasting difficult for human analysts. This volatility creates challenges for commodity traders and analysts in managing risk and achieving consistent returns.
Solution
TerraManta offers a machine learning platform designed to forecast commodity prices and manage capital in volatile markets. The platform analyzes geopolitical news, economic data, and market behavior to identify relationships and predict price movements. By processing thousands of articles and data points, the software provides actionable market assessments and recommended trading strategies. The platform captures market reactions to geopolitical and economic events, leveraging a proprietary machine learning approach called "Reflection of Reality" to forecast price behavior based on repeating patterns.
Target Audience
The primary target audience includes commodity traders, hedge funds, and institutional investors who require accurate commodity price forecasts to manage risk and generate consistent returns.
Features
- Analyzes geopolitical and economic events, supply and demand data, and price actions from structured and unstructured data sources.
- Employs a proprietary machine learning approach, "Reflection of Reality," to identify repeating patterns and forecast price behavior.
- Uses generative AI to provide actionable market assessments and recommended trading strategies.
- Processes over nine years of historical data to train and refine its forecasting models.
- Delivers 21-day price forecasts for WTI front month contract with over 85% accuracy.
- Incorporates motivational analysis of oil-producing and consuming nations to predict market impacts.