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Data-driven AI: how AWS partners and customers operate
From the Ocean Cleanup to Dine Brands, a key factor is driving how these enterprises apply AWS’ technology to their applications and needs.
To clean up more than 200 million pounds of trash in the oceans by 2040, the Ocean Cleanup must be intentional about which areas it targets to fulfill its mission.
The nonprofit organization revealed that it had turned to AWS to provide it with a system that uses satellite data and floating trackers to find ocean hotspots filled with discarded plastics.
"We will combine these data with data that we already have in-house to build a platform that will allow us to steer our ships in the direction with the highest concentration of plastic so we can improve the efficiency of our operations," said Ricardo Farina, head of funding, corporate partnerships, at the nonprofit. AWS will also develop an AI-powered monitoring system so that The Ocean Cleanup can detect marine life and limit harm to it as much as possible.
Farina and other employees of AWS customers and partners were interviewed at the AWS New York City Summit 2025 earlier this week.
While the new collaboration with AWS is centered on AI technology, The Ocean Cleanup is already versed in using AI technology to extract the data it needs for its goal. The group has gathered data on where floating objects or debris are in oceans by installing AI-trained cameras on its vessels.
"[It proves] that AI can help us solve environmental problems," Farina said.
Data foundation at Infor and Equinox
It's also evidence of the importance of data in developing AI-powered tools and applications.
"Having a solid data foundation ... that helps feed successful AI implementations is paramount," said Jeanne Newberry, senior vice president of ecosystem and business development at Infor, a multinational vendor that provides industry-specific enterprise tools and applications. Infor uses the Amazon Bedrock generative AI (GenAI) platform.
One company that shows the importance of a solid data foundation for using AI effectively is Equinox, an international fitness and health chain. Equinox has been an AWS customer for over a decade. using machine learning, personalization models, and Bedrock infrastructure and tools. In recent years, the fitness club has used its member data to create recommendation systems and match its members to various classes.
"When you have a thousand classes and hundreds of thousands of consumers, to say who should take what class, that's just your standard model where you're using propensity," said Eswar Veluri, EVP and CTO at Equinox.
With GenAI, Equinox moved from providing recommendations to updating the conversational UI from a rigid dialogue box to more of a natural language interface. This lets fitness club members ask questions and refine them based on the system's response.
"To be able to type back and that response be understood, assimilated and then providing a modification to the response is the biggest advantage from GenAI because now that makes it a little bit of a two-way system for the end user or a member in this particular case, to feel satisfied with the response," Veluri said.
While Equinox is currently using its current data to inform its AI and GenAI applications, it's also considering how data could inform future use cases of AI technology.
"As we go into longevity, which is something Equinox is trying to do, and longevity has a lot more biometric data and your blood data ... how can AI be leveraged there to provide better recommendations for our members who are aspiring for more of the higher-end services that we're providing?" Veluri said.
Equinox hopes to create better member data for digital twin development to identify members' ideas and goals for the future and visually show what reaching those goals would look like, he added. This means having a proxy of a member to identify fitness goals and needs.
Dine Brands and two types of data
Another company with a long history with AWS that also user data to direct its application of AI technology and GenAI is Dine Brands Global. The company restaurant holding company owns and operates about 3,500 restaurants and has built its digital channels for chains, including IHOP and Applebee’s, on AWS.
"All of our data resides in the AWS ecosystem, so it was a natural fit to work on some of these AI and GenAI use cases and workloads and use AWS accordingly," said Jason Suarez, VP of data services, digital and CRM Engineering, Platforms at Dine Brands Global.
Dine Brands used two sets of data, structured and unstructured, to create external and internal applications.
The unstructured data includes information in SharePoint drives and regular documents.
"It's something that can help some of our tech support agents quickly and efficiently," Suarez said. "They have access to it, but they just can't do it as quickly as they would if they had an assistant."
Using AWS, Dine Brands created the Franchisee Technology Services Assistant, an AI-powered tech support system that helps tech support agents handle service calls from franchisees using natural language.
The second type of data it had was structured data, which stems from its loyalty program at IHOP.
"Naturally, we can offer more personalized services because we have more data from the guest transactions and behaviors," Suarez said. "That's a natural fit where we ... can provide the guests something meaningful and improve our guest experience."
Esther Shittu is an Informa TechTarget news writer and podcast host covering AI software and systems.
