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Uri Yerushalmi Discusses Fetcherr’s AI-Based Airline Fare Suggestions

Uri Yerushalmi Clarifies Fetcherr’s AI-Based Airline Fare Suggestions Amid Industry Debate
This summer, Israeli technology firm Fetcherr became the focus of public scrutiny following remarks by Delta Air Lines president Glen Hauenstein. Hauenstein’s comments raised concerns that Delta might be employing Fetcherr’s AI-driven pricing technology to tailor airline fares based on individual customer data. Delta has categorically denied these allegations, asserting that its pricing strategies do not involve targeting passengers through personal information.
To provide clarity on Fetcherr’s technology and its role in airfare optimization, Airlines editor Robert Silk interviewed Uri Yerushalmi, Fetcherr’s chief AI officer. Yerushalmi detailed the company’s approach and addressed the broader implications for the aviation sector.
The Mechanics of Fetcherr’s AI Pricing Engine
Yerushalmi explained that Fetcherr’s pricing system is founded on a Large Market Model (LMM) that utilizes generative AI techniques akin to those employed in models such as ChatGPT. Unlike language models trained on textual data, Fetcherr’s engine is trained exclusively on aggregated and publicly available airline data, deliberately excluding any customer-specific information, videos, or images.
“Our model functions as a super analyst, capable of making detailed predictions about products like seats and departure dates,” Yerushalmi stated. “It concentrates on forecasting and optimizing prices for the product itself, not the individual customer. For instance, it can simulate demand for a particular departure date and cabin class across various price points, enabling airlines to maximize load factors and improve plane occupancy.”
Commitment to Non-Personalized Pricing
In light of increasing regulatory attention on AI pricing transparency and consumer data protection, Yerushalmi emphasized that Fetcherr does not access or utilize personal customer data. “Absolutely not. No information about specific customers is ever incorporated or leaked into the Fetcherr system. We maintain strict controls to ensure this,” he affirmed. While the system may adjust prices based on ticket attributes such as length of stay or departure date, these adjustments pertain solely to the product characteristics rather than the traveler’s identity.
Airline Adoption and System Flexibility
Fetcherr’s clientele includes prominent carriers such as Delta, Virgin Atlantic, Azul, Jet2, and WestJet, with additional partnerships forthcoming. Airlines retain the ability to impose specific constraints within the model, including setting price limits or preserving established price hierarchies. Despite these customizations, the core AI engine remains consistent across different airline clients.
Industry Impact and Competitive Landscape
The Fetcherr engine’s capacity to analyze a broad spectrum of data points—including public information on market conditions and events at travel destinations—enables more dynamic and responsive pricing strategies than traditional systems. This comprehensive approach allows airlines to adapt fares in real time to shifting market demands.
Nevertheless, the emergence of AI-driven pricing in aviation has elicited mixed reactions. Some consumers express apprehension about the possibility of personalized pricing based on personal data, while others appreciate the potential for more accurate and competitive fares. Meanwhile, competitors in the technology sector are developing similar AI tools aimed at delivering transparent and equitable pricing models as the industry evolves.
As regulatory authorities continue to scrutinize AI pricing transparency and the use of consumer data, companies like Fetcherr face both significant opportunities and challenges in shaping the future landscape of airline fare optimization.

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