Swisscom is Switzerland’s leading provider of mobile, internet, and TV services. In a country of nearly nine million people, Swisscom has more than six mobile connections and two million broadband customers. It’s a household name, but it’s also so much more than a consumer-facing brand. Swisscom provides information and communications technology services to some of the country’s leading enterprises and the buoyant small and medium-sized enterprise sector. It sees its role as empowering Switzerland’s digital future and claims to be the most trusted Swiss technology innovator.
The business plans to invest CHF100 million ($117M) in AI solutions in the coming years. It is working with Nvidia to build generative AI (gen AI) full-stack supercomputers, based on Nvidia accelerated computing and Nvidia AI software. Swisscom wants to take a leadership position in AI, helping find and develop go-to-market AI services relevant to Swiss customers.
As part of this, Swisscom is keen to embrace AI within its own operations and is exploring several use cases.
One particular case is e.foresight, Swisscom’s independent “think tank for the banking industry.” The financial services sector accounts for nearly 10% of the Swiss gross domestic product; e.foresight identifies, monitors, and analyzes trends and behavioral and technological developments in the global financial sector. Used by 30 of the country’s leading banks, it has built up a sizable library of expert content over the years.
Swisscom is using MongoDB Atlas to apply gen AI to this extensive library. The engagement enables Swisscom to extract maximum value from its content, producing bespoke content for the hundreds of e.foresight users within the 30 banks subscribing to its services. By doing so, it is transforming the speed, accuracy, and relevancy of search requests. Rather than forwarding six reports for users to pore over, it can use gen AI to produce a condensed summary within seconds.
“e.foresight has over 3,500 documents about trends in the banking industry in its library, with more being added each day,” said Dr. Martin Lorenz, Product Manager, Banking Front Solutions, Swisscom. “MongoDB Atlas enables us to store and search all that information and create something relevant to a specific request.”
In practical terms, the Swisscom gen AI application needed to enable large language models (LLMs) to make sense of the e.foresight document library. The library is not only large but also diverse. It includes unstructured data, such as written reports, recordings of live events, graphics, and external studies, and it continues to grow.
MongoDB was critical to achieving Swisscom’s goal by helping power its retrieval-augmented generation (RAG) application. Now all documents in the e.foresight library are stored in MongoDB Atlas—a single, secure database for storing and searching vectors alongside operational data. Swisscom can then convert the unstructured data into vector embeddings and use MongoDB Atlas Vector Search to find segments of relevant context to feed the LLMs up-to-date contextual, domain-specific data. As a result, the application can generate more accurate, highly relevant responses for users.
In a fast-moving industry, with constant breakthroughs in gen AI capabilities, MongoDB empowered Swisscom to move quickly from idea to production, enabling faster speed to market. Lorenz reached out to MongoDB on February 6, 2024, and had a prototype based on a subset of data fully built on the MongoDB Atlas Developer Data Platform by February 15. After a month of testing alongside MongoDB and the university of applied science ZHAW, the Swisscom internal team took over the platform operations.
The team added new features, and after another month of in-house testing, the platform went into production in early May.
Dr. Martin Lorenz, Product Manager, Banking Front Solutions, Swisscom
The success of the project has, first and foremost, improved the e.foresight experience for subscribers. Rather than pointing users to a 4,000-word article, the application can use gen AI to efficiently extract and accurately summarize specific content from multiple sources. Additionally, the team has found that the difference in relevancy of answers via AI is “night and day” compared to content produced by ChatGPT, feeding from general online sources.
“Our answers are much more concrete and accurate. Any industry, but particularly the banking industry, wants solid answers, reliable sources, and up-to-date metrics,” said Lorenz.
The quality of answers will only improve as the platform is refined. Users can uptick answers, helping flag accurate searches and train the model for better results. All content also includes links to source material. “It’s important we demonstrate we’re a partner of trust,” Lorenz added.
The rate at which the e.foresight library adds new content will also increase: it will apply gen AI to help write new-trends analyses, and refine content based on user activity. The gen AI application will have more and better-quality content to consume. Ultimately, Swisscom has found that e.foresight is seen as a progressive, user-focused, and more-trusted source for valuable insights in the banking industry.
At a broader level, the project has enabled Swisscom to demonstrate its progress in creating meaningful AI use cases. The company is not just investing money in AI but is also taking practical steps to upskill its teams and develop services relevant to its target markets. The company now has a variety of AI projects underway, from chatbots to search to content creation.
Lorenz explained that the experience on e.foresight will play out across Swisscom. As part of its Swiss AI Platform, the company is launching GPU Rental, GenAI Studio, and AI Work Hub, all services aimed at encouraging the uptake of AI among Swiss enterprises.
Dr. Martin Lorenz, Product Manager, Banking Front Solutions, Swisscom