Founded by experts rooted in deep learning, algo-trading, e-commerce and digitization of legacy architecture, Fetcherr is an Israeli tech company that developed a proprietary AI-powered pricing and inventory control engine that accurately and granularly predicts demand and enables high frequency pricing for the airline industry.
PhocusWire coverage
- Fetcherr partners with Brazilian airline Azul Airlines to pilot Fetcherr’s demand prediction and algorithm pricing technology.
- Fetcherr partnering with ATPCO to incorporate its current and historical fare data into its algorithms.
Strategic goals for 2023
We are not a company from the travel industry. We are tech people that offers a different approach to the challenges the industry is facing. In 2022 we launched successfully with Azul our solution for low-cost airlines, and in 2023 we will launch with our leading partners our solution to legacy and ULC airlines as well. Today we are enabling our customers to price granularly not only routes but also flights. During 2023 we will enable our customers to price ancillaries and even seats on autopilot. As a growing startup, our scaling strategy is to sign up during 2023 5 more leading airlines.
Lessons learned since founding
In the past three years while being in stealth mode, we trained our engine with millions of data points from the airline industry. This process taught us many insights of how the industry operates and what its vulnerabilities: When using a cutting-edge deep learning technology, we believe that a startup needs first to develop a live product, validate it – and only then address investors and clients.
Most people do not understand technology and need to see not only a vision or intention, but a true, working product that proved to give measurable added value, before agreeing to participate. Also, we understood that even more important to address the need of technology is to address the fear of technology. We had to invest most of our efforts to decrease the risk and increase the trust of our clients by developing innovative solutions such as explainable AI (glass box and not a black box approach), piggybacking on existing systems and not replacing them, remote onboarding, gradual scaling, etc. We simplified proven science methods from capital markets to provide airlines RM teams tools to self-validate the system’s results in real time.
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