The new SAP HANA Cloud vector engine enables businesses to combine the power of large language models (LLMs) with company-specific, real-time data and business process know-how, all integrated in one multi-model database: SAP HANA Cloud. With the latest quarterly release, the vector engine is now generally available.

SAP HANA Cloud is a market-leading database-as-a-service enabling intelligent data applications and is one of the most adopted services within SAP Business Technology Platform (SAP BTP) internally at SAP. As of today, more than 180 different applications and services use SAP HANA Cloud with its multi-model capabilities.

Now, SAP HANA Cloud is also a leader in the generative AI age.

At SAP, we work with various LLMs such as GPT-4, Llama2, Falcon-40b, and Claude2. While these models offer amazing opportunities, they also have limitations. For example, LLMs may rely on outdated training data and lack company-specific data and business process context.

As an example, imagine having an LLM as a colleague. This colleague would be very intelligent, able to program, pass exams, or have arguments – but this colleague would not know anything about what happened in the world in the past year, nor have any idea about internal processes of your company or any of your systems. Even worse, after every conversation you have, this colleague would forget what you just talked about. Working with such a lack of memory would be of limited value. This shortcoming is why an LLM cannot answer easy questions like “What do you think about the offer from our most important supplier last week?” An LLM can only work with the initial training data – all other data must be provided as context.

Supplementing this lack of information is where SAP HANA Cloud vector engine can assist. The engine can provide LLMs with all the relevant data of an organization through a process called “retrieval-augmented generation.”

A Game-Changing Feature

So how does the vector engine work? It is a new addition to SAP HANA Cloud’s multi-model engines, enabling customers to utilize the similarity between two or more vectors to solve business problems. With the integration of AI-focused technology, SAP HANA Cloud can now empower businesses to combine intuition along with data-driven insights to solve even the most complex of problems.

Some key benefits and features of the vector engine include:

• Multi-model: Users can unify all types of data into a single database to build innovative applications using an efficient data architecture and in-memory performance. By adding vector storage and processing to the same database already storing relational, graph, spatial, and even JSON data, application developers can create next-generation solutions that interact more naturally with the user.
• Enhanced search and analysis: Businesses can now apply semantic and similarity search to business processes using documents like contracts, design specifications, and even service call notes.
• Personalized recommendations: Users can benefit from an improved overall experience with more accurate and personalized suggestions.
• Optimized large language models: The output of LLMs is augmented with more effective and contextual data.

The Database Foundation of SAP’s Generative AI Strategy

The addition of the vector engine establishes SAP HANA Cloud as the default database in SAP’s generative AI solution strategy. Customers can create the next level of user experiences along with other services within SAP BTP. As an example, SAP BTP can provide centralized access to SaaS-based LLMs from multiple vendors as well as host LLMs from open-source models or third parties. The generative AI hub in SAP AI Core, a capability that facilitates the use of generative AI capabilities, will soon rely on SAP HANA Cloud as the primary vector storage. One function of the generative AI hub feature is to help provide a process for creating embeddings and storing the resulting vectors in SAP HANA Cloud. Customers building intelligent data applications can use both services together to augment LLM queries with relevant context for meaningful answers.

SAP is working on foundation models that are specific for SAP-related industry and process knowledge.

The Database for Innovation

SAP HANA Cloud continues to lead the market by storing and processing different types of relevant business data – all within the same database. The new vector engine, combined with other multi-model capabilities, opens a world of possibilities for applications to help enhance the execution of business processes. Whether improving search capabilities, gaining deeper insights for informed decisions, or optimizing LLMs, SAP HANA Cloud enables the type of applications that can elevate the expertise and effectiveness of every user.

To learn more, sign up for an introductory webinar on April 4. Do you already have a use case for SAP HANA Cloud vector engine in mind? If so, consider registering for the SAP Early Adopter Care program.

Juergen Mueller is CTO and member of the Executive Board of SAP SE, Technology & Innovation.
Stefan Baeuerle is head of Database, SAP HANA Database, & Analytics for Technology & Innovation at SAP.

Carbon footprint calculation, patient privacy, and machine learning based on sensitive data – thanks to advanced encryption methods like fully homomorphic encryption.

Most have been in this situation before: one of the providers or services we use is a victim of a data breach and we want to determine if our personal user data has been impacted. This is where fully homomorphic encryption (FHE) comes into play. With FHE, the encrypted, personal password is compared against the data set of stolen user data and potential matches are identified without ever revealing the user’s password.

Use cases for this type of privacy-enhancing technology (PET) are numerous. They range from applications in medicine, where third-party service providers can analyze health data without compromising a patient’s privacy, to performing machine learning and AI algorithms on encrypted data, allowing organizations to derive insights from sensitive data sets without exposing the data to potential breaches or privacy violations.

How It Works

Fully homomorphic encryption allows calculations to be performed on encrypted data without having to decrypt it first. Confidentiality is maintained, as even the results are encrypted and can be viewed only with the appropriate decryption key. Further techniques for processing encrypted data are multi-party computation (MPC) and trusted execution environments (TEE).

Mathias Kohler, research manager at SAP Security Research, outlines the differences: “While FHE is the most known of the encryption technologies, MPC is the ideal candidate if working with several parties exchanging encrypted data across company borders. And it can be substantially faster than FHE.” While both are software-based technologies, TEE is hardware-based, which makes it the fastest choice. The downside: TEEs, unlike MPC and FHE, require decrypting the data for processing. While decryption happens in a trusted hardware environment isolated from the operating system, it can allow data leakage via side-channel attacks. Notably, PETs do not need to be considered in isolation and can augment each other. For example, MPC can encrypt and distribute an FHE decryption key, protecting the FHE key and ensuring no single party can decrypt everything.

Why It’s Relevant

There is a demand for this kind of technology. By 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing, according to Gartner.

Fully homomorphic encryption has numerous applications, especially in scenarios where privacy and security are paramount, such as secure computation in the cloud, privacy-preserving data analysis, and secure outsourcing of computations. As long as one party is performing the data processing centrally, FHE is the encryption method of choice. FHE enables organizations to share encrypted data with partners or third parties for analysis or monetization purposes while maintaining data confidentiality. This is particularly relevant in industries such as advertising and market research.

Interesting use case scenarios from SAP’s perspective could be secure benchmarking and predictive maintenance.

Secure Benchmarking

Companies often assess their competitiveness relative to industry peers and compare business-relevant KPIs, such as automation rate or return rates, with peers and even competitors. With fully homomorphic encryption, all participating parties can share encrypted KPIs without revealing individual data. As a result, they learn about relevant statistics, such as averages or medians, to assess their relative competitiveness and decide where to improve and invest.

Predictive Maintenance

Predictive maintenance is a machine learning technique to forecast demand for maintenance or spare parts based on historical data. “In certain industries, required data, such as usage patterns and failures, is considered sensitive and is not easily shared with data scientists or maintenance operators,” says Anselme Tueno, senior researcher at SAP Security Research. By computing on encrypted data, however, no sensitive information is revealed while still allowing for the required insights to be gathered for prediction tasks.

Carbon Footprint Calculation with Multi-Party Computation

While it is early days from a product availability perspective, SAP is working on potential use cases with customers and partners. One key example is calculating carbon footprints of products.

Prime examples for complex collaborations are today’s supply chains, intricate networks that encompass various levels of suppliers, manufacturers, and processed goods. Unfortunately, there is often a lack of comprehensive visibility across the entire process – either for technical reasons or because businesses are often reluctant to share sensitive data across supply chains that often include direct competitors.

However, to accurately assess and disclose a product’s carbon footprint, sensitive production details and associated carbon costs for production-relevant parts and materials are required. Here, MPC can reveal only the required carbon footprint without disclosing associated, proprietary manufacturing details with other supply chain participants.

Currently, SAP is working with Bosch on cloud-native software for secure multi-party computation called Carbyne Stack.

“SAP participates in this open-source project and supports the development of Carbyne Stack’s storage and processing services and the deployment of Carbyne Stack on Amazon Web Services (AWS),” Kohler explains. “For Bosch, Carbyne Stack is a type of cloud-native operating system for MPC workloads that manages resources to run as efficiently as possible in multi-cloud deployments.” This effort can help SAP in the long run to integrate MPC as technology into SAP solutions and services while running in a cloud-native environment.

What’s Next?

Despite all the benefits around processing data, encryption introduces significant computational overhead due to the complexity of performing operations on encrypted data. Slow processing speeds, especially for complex operations and large data sets, makes fully homomorphic encryption impractical for real-time applications or large-scale data processing. Although the performance of FHE has greatly improved in recent years, its practical adoption is still limited due to the processing overhead and performance considerations. Ongoing research is focused on the design of FHE-specific hardware accelerators.

“PETs for computing on encrypted data have the power to amplify data-driven business collaborations and reshape the future of cloud computing,” explains Jonas Böhler, senior researcher at SAP Security Research. By safeguarding data, they enable access to previously untapped information while minimizing privacy risks and thwarting data breaches. The future of computing is encrypted.

In a merger between two well-matched organizations, cultural integration can be the key to successfully transforming into a single high-performing entity ready to take on new opportunities. Notably, more than a few high-profile mergers have failed due to cultural incompatibility. Add a third organization into the merger and the cultural complexities increase exponentially. But some multi-organization mergers do successfully navigate these challenges and reap the transformational benefits.      

Convista, a consultancy and SAP partner based in Cologne, Germany, emerged stronger and better positioned to serve its clients following a recent merger that brought together three former consultancies: Axxiome Health, ConVista Consulting, and enowa. With 25 years of experience delivering transformation projects to its clients, Convista used that expertise in its own rebranding to present its capabilities to clients and employees: a vibrant people culture as well as a respected and trusted brand supported by SAP S/4HANA Cloud Public Edition for ERP and SAP SuccessFactors Employee Central for core HR.

“Trust and transparency are common values that we share at Convista,” declares Convista CEO Martin Hinz. “Combined with a dynamic team spirit and passion, it’s what we bring to our clients every day.”

With a workforce of around 1,200 employees, Convista has made a name for itself through its dedication and expertise providing end-to-end solutions to clients throughout the world with a presence in Germany, Austria, Switzerland, Poland, Spain, Brazil, Israel, and further locations across the globe. It supports client projects primarily in four sectors: insurance, industry, healthcare, and energy/utilities. In recent years, Convista has twice been awarded SAP Partner of the Year in the Financial Services sector.

“At Convista you meet everyone on the same level, independent of your skill level or where you are in your career,” says Stefanie Weber, project lead of People and Culture – HR Systems, Convista. “Also, when we’re working with customers, we try to approach them at eye level, which makes quite a good working environment. The implementation of SAP SuccessFactors came as a natural extension to our brand and our culture.”

The Challenges of Data Siloed in Three Systems

Weber says one of the reasons she joined Convista in 2012 while studying business at university was the high priority its leaders place on trust and transparency, values that permeate the entire organization and empower employees in their work and career development. “Trust is one of our main values,” she underscores. “Also, the trust that people are willing to do their best to get motivated and move the company ahead.”

Convista grew quickly both organically and as a result of mergers with other consultancies. In 2019, IT service provider Axxiome Health joined the ConVista Group to deepen the organization’s expertise in the health insurance sector. In 2021, enowa joined the group, infusing its knowledge of industries and insurance. With the mergers complete, the incipient organization became the new Convista on January 1, 2023.

Though team members were highly motivated to collaborate from the start, Convista’s vision for itself as a modern organization was held back in both its daily work for projects and internal services. Using disparate tools based on older technology and a patchwork of third-party solutions that lacked integration proved to be inefficient and unsuitable as a basis for decision-making.

“Whenever we wanted to have a report, even something as simple as a headcount, we always had to go into three different systems, collect the data, and report on that,” Weber recalls. “It’s just one of the many examples of why we really urgently needed one IT platform.”

Project ONE Achieves Milestone Integration

To build a strong foundation for future growth, Convista embarked on “Project ONE” with the goal to have one digital platform flexible and powerful enough for the entire organization. For this, it chose SAP S/4HANA Cloud Public Edition and SAP SuccessFactors solutions with self-service capabilities for employees to log time-off.

Overall, implementing SAP SuccessFactors Employee Central with SAP S/4HANA Cloud Public Edition can result in streamlined HR processes; end-to-end integration with seamless connectivity between HR and finance functions for accurate and up-to-date employee data across the organization; greater transparency of data for analytics and reporting on workforce trends, costs, and profitability to enable better strategic planning and resource allocation; and compliance with regulatory requirements and data security.

Among the key advantages is the ability for employees to access their own HR-related information, such as personal details and time-off balances. This self-service capability helps empower employees, improve transparency, and enhance the overall employee experience.

Convista’s project team decided for a phased approach to the implementation by first introducing the SAP solutions in Poland and later in Germany, Austria, and Switzerland – with SAP S/4HANA Cloud Public Edition planned to launch in the German-speaking countries during the course of 2024. To optimize success, the project team used the combined best practices of Convista and SAP and hosted regular meetings that provided clear communication to steer the project. “We were always aligned on the requirements of the other teams,” says Weber, who managed the HR workstream. “We all knew the main goal of the implementation. This was helpful for everyone on the project.”

In-house experts from Convista certified on SAP SuccessFactors solutions contributed valuable knowledge for the implementation. Consultants from SAP Services and Support successfully integrated the cost center replication from SAP S/4HANA Cloud to SAP SuccessFactors and the workforce replication from SAP SuccessFactors to SAP S/4HANA Cloud, and delivered a detailed administration guide on the integration setup for Convista. Additionally, they provided an overview, the architecture guidance, and the navigation through major hurdles in performing the configuration to set up identity access governence (IAG), identity provisioning service (IPS), and identity authentication services (IAS). The SAP Early Adopter Care program supported Convista for the master data integration (MDI) during the implementation and helped to solve all roadblocks efficiently.

On January 1, 2023, Convista’s 80-person team in Poland was the first to go live with the new SAP solutions. “It was really a great experience for them and quite an advancement,” says Weber, citing the benefits of the new solutions that provide optimizations and intuitive workflows. The project took a pivotal turn on January 1, 2024, with the launch of SAP SuccessFactors solutions for Convista’s 800 employees in the German-speaking countries.

“The biggest milestone was to have [SAP S/4HANA Cloud Public Edition and SAP SuccessFactors Employee Central] speaking with each other,” says Weber, who emphasizes how valuable it is for the team “to have an end-to-end process within one platform.” With an integrated IT platform in place, she says that it is no longer necessary to do workflows, authorizations, or any other processes in other systems.

The seamless synchronization of data by using a common data model for SAP business applications helps reduce the need for manual data entry and redundant processes. This means, for example, employee data that is maintained in SAP SuccessFactors Employee Central is available in real-time in SAP S/4HANA Cloud Public Edition; while master data, like cost center data, flows seamlessly from SAP S/4HANA Cloud Public Edition to SAP SuccessFactors Employee Central. Eliminating data silos enables the HR and finance teams to work with consistent, accurate data for all-important employment decisions and legal reporting obligations.

Now Convista’s team is unified in its brand, values, spirit – and employee data. 

More Transparency and Intuitive Workflows Are Just the Beginning

Feedback has been overwhelmingly positive, according to Weber, with employees speaking favorably about the improved transparency and workflows. “The first thing I heard from everyone was, well, this is simple and intuitive. They were so happy about it,” she says. “They are big fans of the mobile application. They find it very transparent and easy to use.”

For some colleagues, the new solution lets them view their own data for the first time. “When we went live, everyone was viewing their profile,” says Weber. “This was also quite new that you are able to see what data is maintained for your person, your address, but also job information – to view it and have this transparency. People like this very much and also the ability to have the self-services in SAP SuccessFactors.”

To strengthen communication between HR and employees, Convista will bring more people processes onto the new digital platform. In fact, the team very recently implemented the SAP SuccessFactors Performance & Goals solution for annual employee appraisals, goal setting, and project feedback. “It’s just the beginning,” Weber says. “There’s still a lot of work ahead of us.”

Hinz says, “We have been careful to preserve our workplace culture during the transformation. Now that we are rebranded as one organization, we are seeing the benefits of that early effort. With SAP, we now have the digital platform to build people-centered processes that advance our vision as a unified, high-performing organization serving our clients.”       

Find out more about SAP SuccessFactors solutions.

Jacqueline Prause is a journalist at SAP.