Discovering the AI & Data Foundation with SAP HANA Cloud

In the age of artificial intelligence, data is more critical than ever. However, enterprise data is often fragmented across systems, stored in different formats, and lacks semantic business context. This makes it difficult for AI solutions to deliver accurate, relevant, and trustworthy results. SAP Business Technology Platform addresses this challenge by providing an Data & AI Foundation that connects data, AI capabilities, and applications in a governed way.A critical part of this foundation is SAP HANA Cloud. It acts as the central data platform that connects business data with AI use cases, intelligent applications, and autonomous agents.

Modern AI scenarios require more than raw data to provide value in an enterprise context. To be effective, AI applications need semantic business context, unified access to different data types, scalable processing, and trusted governance. SAP HANA Cloud is designed to meet these requirements by acting as a single grounding layer for AI applications and agents.

The core strength of SAP HANA Cloud lies in its powerful multi-model engine. Transactional, analytical, spatial, graph, and text data can be combined with native vector capabilities in one database. This integration is especially important for generative AI scenarios where text data must be processed directly in the database to create embeddings that capture semantic meaning.

By executing similarity searches alongside SQL and graph queries, developers can significantly simplify AI workflows. Instead of managing multiple databases and complex data pipelines, they connect to a single service that supports everything from standard SQL to SPARQL and vector search, reducing overall architectural complexity.

SAP HANA Cloud increasingly supports AI-driven interactions through specialized database agents. These agents assist with specific tasks such as discovering relevant data artifacts, understanding complex data relationships, and supporting administrative operations. To ensure accuracy, AI scenarios are grounded on a solid foundation represented by an automatically generated knowledge graph built on custom enterprise data. This ensures that agents operate with the correct context and a deep understanding of the specific business domain.

To make data even more accessible to AI agents and large language models, SAP HANA Cloud supports the Model Context Protocol (MCP). This protocol allows Joule agents, custom agents, and AI models to access the rich multi-model engines of SAP HANA Cloud directly. The support for MCP enables the autonomous orchestration of tasks across the entire data ecosystem. This integration ensures that while AI agents perform complex tasks, enterprise governance and security standards are maintained at all times.

For AI agents to deliver real value, they must maintain context across multiple interactions. SAP HANA Cloud provides persistent, long-term memory for AI agents, often referred to as agentic memory. This capability enables agents to remember important facts from previous interactions and maintain context across long-running conversations. As a result, agents can continuously improve their reasoning and decision-making processes. This leads to a more personalized and consistent user experience, where agents learn over time and act with greater precision based on historical data.

In conclusion, SAP HANA Cloud serves as the AI-native data foundation of SAP BTP, effectively connecting enterprise data with intelligent applications and agents. By utilizing its integrated multi-model engine, the platform simplifies technical architectures by processing vector, graph, and transactional data within a single system. Furthermore, the support for the Model Context Protocol enables AI agents to interact directly with the database engines, while agentic memory provides the necessary long-term context. This foundation allows agents to continuously improve their reasoning and deliver a more precise, personalized user experience over time.