From crowds to connection

As its fan base continues to evolve and grow, the Cubs wanted to be able to recognize, understand, and connect with every fan while maximizing ticket sales.

Diving into their customer data, we combined human insight and machine learning analysis to develop an effective customer segmentation model and 12 customer personas. The Cubs can now confidently create new, engaging experiences that win hearts and drive business growth.

From carbon to clarity

We partnered with a large renewable energy company to methodically test, measure, and build its most innovative AI ideas to support an ambitious and incredibly important goal: a decarbonized future.

In just eight weeks, we helped the company identify and prioritize 36 use cases, representing tens of millions in value. Leaders now have a process for rapidly scaling the right ideas across the organization and business cases for every idea moving into production.

From risk to reliability

While Kawasaki has been manufacturing large machinery for 100+ years, the company is now taking on a new challenge: making it easier (and less expensive) for US rail companies to keep their tracks safe.

In collaboration with several of our technology partners, we helped Kawasaki develop a new product for its Track Maintenance Platform. Using AI and ML, this new product provides deeper insights into freight rail conditions, leading to more efficient maintenance efforts.

From escalations to ease

We partnered with Virgin Voyages, a luxury cruise line, to develop Vivi, one of the first generative AI-powered digital humans built on Salesforce.

With the launch of Vivi, Virgin Voyages elevated its customer experience, alleviated management costs, and reduced call center escalations by more than 20%, reshaping the typical chatbot experience and setting a new standard for online customer service.

From possibility to prevention

We used machine learning (ML) to help advance Hologic’s digital cytology platform, enabling it to autonomously detect cancerous or pre-cancerous cells in patient samples. 
 
The result was a proof-of-concept algorithm that autonomously determined slide-level classification of pap test images with ~70% relative sensitivity compared to human review, helping promote earlier diagnosis and treatment of cervical cancer.

From crisis to coordination

Using AI, we helped create a fast and thorough way for the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) to review project proposals so that people get the help they need during humanitarian crises.

In less than three weeks, we built a successful proof of concept that would help OCHA direct funding where it’s needed most, as well as share insights with donors. 

From paperwork to precision

As part of the Machine Learning Embark program, we partnered with AWS to help Celink determine its highest-value use cases, leading to 121% ROI over three years. 
 
The proof of concept we codeveloped automated Celink’s process for filing mortgage loan defaults to initiate foreclosure with 97% accuracy, while keeping humans in the loop. We also helped upskill 22 business and technical executives as well as 16 technologists on Celink’s team. 

From turbulent to trustworthy

We helped one of the world’s largest airlines implement generative AI, developing solutions that empower their employees and elevate the customer experience.

The result? Customer service efficiencies and greater transparency for travelers that helped strengthen customer trust and dramatically improve the company’s net promoter score.