Company Overview
Snapshot
Founded in October 2011 by Igal Zivoni, Meteo-Logic operates with 11–50 employees. The company has raised $17.2 million across three funding rounds from three investors. In February 2021, Meteo-Logic secured convertible debt funding.
Business overview
Meteo-Logic develops an energy asset trading platform that leverages global weather data and other big data sources with machine-learning algorithms. The company aims to bring stability and predictability to the energy ecosystem and restructure energy markets to meet universal needs. Meteo-Logic provides its proprietary trading AI engine to futures hedge funds, enabling them to capitalize on trading opportunities in energy commodity markets. The company operates within the Fintech & Insurtech sector, specifically focusing on Trading & Investing, and also has relevance in Climate Tech, Carbon Analytics, Earth Data & Fintech, and Energy Transition.
Strategic signal
In February 2022, Meteo-Logic's strategic evolution from a weather prediction algorithm to a power futures trading system was highlighted. This shift demonstrates the company's ability to adapt its core technology to capitalize on high-value financial markets, signaling a strong commercial focus and potential for significant revenue generation in the energy trading sector.
Company Intelligence Q&A
- What is Meteo-Logic's core business?
- Meteo-Logic leverages global weather data and machine-learning algorithms to power an energy asset trading platform, aiming to provide stability and predictability to energy markets.
- Who founded Meteo-Logic?
- Meteo-Logic was founded by Igal Zivoni in October 2011.
- What was a significant financial event for Meteo-Logic in 2021?
- In February 2021, Meteo-Logic secured convertible debt funding from Clean Value Ventures.
- How much capital has Meteo-Logic raised in total?
- Meteo-Logic has raised a total of $17.2 million across three funding rounds.
- What was a key strategic development for Meteo-Logic in 2022?
- In February 2022, Meteo-Logic's transition from a weather prediction algorithm to a power futures trading system was highlighted, showcasing its strategic pivot into energy commodity markets.