Artificial Intelligence (AI), large market models (LMM) and big data have all become buzzwords, making an appearance in most conversations about business.
However, practical, quantifiable examples of real-world applications are harder to come by. It doesn’t matter how much space companies devote to talking about AI in their annual reports and strategic plans. The sad reality is that most AI projects, in fact, fail to leave the pilot stage or don’t integrate with the business mainframe.
Perhaps not unsurprisingly, given the industry’s track record in early technology adoption, it was an airline that provided one of the earliest cases of success and, what’s more, has chosen to showcase this success as a case study for the industry
The collaboration between tech startup Fetcherr and Brazilian airline Azul is the rare exception that proves the rule: AI can actually work at scale and deliver very tangible financial results.
At the World Aviation Festival 2025 in Lisbon (October 7-11, 2025), the two companies showcased their success story, offering attendees a glimpse at the power of large market models (LMM) when applied to airline pricing. André Américo, Director of Planning & Revenue at Azul Airlines, and Dr. Uri Yerushalmi, Chief AI Officer at Fetcherr, presented their collaboration on stage.
After the presentation, the two experts sat down with AeroTime to discuss how they successfully deployed LMM technology at Azul, one of Latin America’s largest carriers, operating nearly 200 aircraft and carrying around 30 million passengers in 2024.
“The key was doing it step by step, adding one market at a time and scaling it up,” explained Américo, who revealed that the airline achieved a 3-5% revenue uplift from the moment it began deploying Fetcherr’s technology.
This technology was progressively scaled up by Azul until it covered around 50% of its operations, then it was rolled out across the entire business.
Américo explained that the actual technology rollout, for which Azul also had the full support of Fetcherr data scientists, was actually the easy part. The most challenging aspect was getting a highly experienced team, which was already high performing in its own right, to change its mindset and embrace this new tool and framework.
“We are wasting less time and inputting information into the system and have a lot more time to strategize and find ways to align our revenue management function with other marketing initiatives,” Américo explained, dismissing any lingering fears about AI-induced disruption in corporate environments. Américo also explained how, in addition to boosting revenue, Fetcherr’s LMM has saved around 10% of his team’s manual overhead. Analysts can now allocate this time to work on other high value projects.
This effectiveness can be attributed, in no small measure, to Fetcherr’s tailoring of its LMM to fit the specific needs of Azul, and of the airline industry more generally.
In this regard, Dr. Yerushalmi highlighted how the model is trained with a large amount of market data, which makes it accurate for airline pricing purposes.
“It is doing endless simulations, scanning possible decision making and choosing the right pricing policy,” he explained, adding that Fetcherr’s LMM helps airlines like Azul connect the dots about what is happening in the market.
Fetcherr helps airline revenue managers like Américo do less firefighting and focus on strategizing. However, Dr. Yerushalmi was also keen to highlight that the same principles and technology are suitable for other airline functions that require data-based complex decision-making.
This has not gone unnoticed in the investment community. In September 2025, Fetcherr closed a $42 million Series C funding round led by Salesforce Ventures, which will help it expand in the airline industry as well as in other verticals.
Having demonstrated the power of its LMM in one of the most fiercely competitive industries, Fetcherr is now ready to help companies in other industries make better pricing decisions.
You can watch the full interview below.