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Fetcherr raises $12.5 million to help airlines increase revenue with AI-powered pricing system

Fetcherr raises $12.5 million to help airlines increase revenue with AI-powered pricing system

The Israeli Algo Trading-based startup has developed an AI-powered pricing system, using reinforcement AI models to increase airline revenue by enabling High-Frequency Pricing

CTech | 16:02, 04.04.23

Fetcherr, a demand prediction and AI-native algorithmic pricing optimization solution, announced on Tuesday a $12.5 million Pre-Series B investment led by M-Fund with participation from Left Lane Capital. M-Fund also led Fetcherr’s $7 million Series A in 2022. This round brings Fetcherr’s total funding to $31 million across equity and debt.

Full list of Israeli high-tech funding rounds in 2023

Fetcherr is an Israeli Algo Trading-based startup that developed an AI-powered pricing system, using reinforcement AI models to increase airline revenue by enabling High-Frequency Pricing. Founded in 2019 by experts in deep learning, Algo-trading, e-commerce and digitization of legacy architecture, Fetcherr aims to disrupt traditional, rule-based (legacy) revenue systems through deep learning methodologies, beginning with the airline industry.

Lior Elkan. Lior Elkan. Lior Elkan.

The new funding will allow Fetcherr to onboard additional airline partners, open a North American headquarters, and further expand into other global markets.

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"Due to the global quarantine, the demand for flights plummeted, which caused a chain reaction of the collapse of legacy revenue management systems and the significant labor dismissal in the aviation industry,” said Lior Elkan, Managing Partner at M-Fund. “The new atmosphere forced airlines to rethink their operations and opened an ideal entry point for Fetcherr to solve the industry's broken infrastructure. M-Fund led the rounds in the past year to back four talented and experienced founders who perfectly completed each other and came up with a unique angle from the AI-based algo-trading discipline to implement a one-of-its-kind dynamic real-time pricing system.”

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