Introduction:
In continuing the exploration of innovative SAP HANA Cloud vector engine implementations, we now turn to another remarkable example from LeverX. LeverX from SAP Partner Ecosystem has developed an innovative solution as part of the SAP BTP Gen AI Lighthouse Program. Continuing from Wipro and Deloitte’s success stories, this blog explores how LeverX leverages the SAP HANA Cloud vector engine to transform operations and boost efficiency across industries. LeverX has implemented the Unstructured Data Intelligent Assistant solution, addressing challenges in searching and analyzing unstructured data stored in custom formats, helping companies streamline and optimize production design processes.
Use Case: Unstructured Data Intelligent Assistant
Problem Statement:
Most companies face challenges in effectively searching, navigating, and analyzing unstructured or custom data stored in various formats such as CAD and PDX. They struggle with the lack of embedded tools for searching through local custom repositories and cloud data storage containing unstructured or packed data. Additionally, data management issues, such as the creation of duplicated data instead of reusing existing templates, further complicate the process. Complex tools make it harder for users to use natural language prompts for efficient data search and analysis across both SAP and non-SAP platforms.
Solution:
LeverX designed an Unstructured Data Intelligent Assistant solution on the SAP BTP platform that, according to the company, seamlessly integrates ERP data sources, utilizing efficient data preparation methods and harnessing the SAP HANA Cloud vector engine for advanced storage and vector-based search capabilities. It leverages SAP BTP’s request processing layer, utilizing the SAP Generative AI Hub to transform natural language prompts into SQL queries and performs vector search against vectorized information in HANA Cloud, enabling efficient and accurate data retrieval. The processed data is then visualized and made accessible through a flexible Intelligent Assistant component.
The Intelligent Assistant operates in two modes: Standalone Mode and Embedded Mode. In Standalone Mode, it functions independently, providing powerful search and analysis capabilities through APIs, allowing users to interact with unstructured data across various platforms. In Embedded Mode, it integrates seamlessly within SAP systems, enhancing the ability to search and analyze unstructured data directly within the SAP environment.
This dual-mode functionality ensures that the Intelligent Assistant can be integrated across different workflows and systems, whether on SAP or non-SAP platforms. By supporting both standalone and embedded deployment, this solution addresses the lack of ready-to-go tools in the market, significantly reducing the effort required to search through files in proprietary formats.
LeverX created the solution to help non-technical users analyze proprietary data more effectively, support better data management practices, and reduce duplication through the reuse of existing templates to enhance operational efficiency and decision-making processes.
Solution Overview:
Reference Architecture:
Value Add of SAP HANA Cloud vector engine:
The SAP HANA Cloud Vector Engine plays a crucial role in the Intelligent Assistant solution by enhancing the capabilities of searching and analyzing unstructured data. Here’s how it is used in this context:
Vector-Based Search Capabilities: The SAP HANA Cloud vector engine powers similarity searches by interpreting the semantic meaning of queries, making it more effective in retrieving relevant information from unstructured data like PDFs, CAD files, and PDX files, compared to traditional keyword searches.Handling Unstructured Data: Unstructured data often lacks a predefined schema, making it challenging to search and analyze using conventional methods. The vector engine addresses this challenge by supporting the storage and querying of vectors (obtained from embedding the unstructured data) that capture the context and relationships, enabling accurate and efficient searches even with large and varied datasets.Enhanced Data Retrieval: The vector similarity search capability allows the Intelligent Assistant to find data based on conceptual similarity rather than exact matches, making searches with natural language prompts more intuitive and user-friendly.Integration with Natural Language Processing: The vector engine works in conjunction with the SAP generative AI hub, which processes natural language queries into SQL and performs vector search against vectorized information in HANA Cloud. The vector engine performs the search and retrieval process, allowing users to ask complex questions in plain language. It provides precise answers, even when the underlying data is unstructured and distributed across different repositories.Integration Across SAP and Non-SAP Systems: The vector engine’s integration with SAP BTP allows for seamless access and retrieval of data across both SAP and non-SAP systems, ensuring comprehensive search capabilities across all relevant data sources.
Conclusion:
Our partners, such as Wipro, Deloitte, and LeverX, are leveraging the SAP HANA Cloud vector engine and SAP BTP services to create innovative solutions that drive real value for our joint customers across various industries. These collaborations showcase how the power of SAP technologies is transforming business operations and enabling new levels of efficiency and insight. From enhancing AI-driven solutions to improving data management and analytics, each partner’s use case has showcased the transformative potential of using SAP HANA Cloud to power intelligent data applications. With the insights shared in this series, I hope to have provided a comprehensive understanding of how SAP HANA Cloud can be leveraged to solve real-world challenges. Keep an eye out for future events as we keep exploring the exciting and ever-changing world of technology powered by the in-memory database.
Note: This blog is a collaborative effort between SAP HANA Cloud Product Management and LeverX, highlighting the innovative solution developed by the LeverX team: Vitali Usau (vitali.usau@leverx.com), Dzmtry Buriak (dzmitry.buriak@leverx.com), Pavel Lazhbanau (pavel.lazhbanau@leverx.com), Siarhei Valenda (siarhei.valenda@leverx.com). For those interested in learning more or exploring implementation details, please feel free to reach out to the mentioned team member contacts.
References:
Try for yourself:Explore SAP HANA Cloud Vector Engine via Basic TrialHarnessing Generative AI Capabilities with SAP HANA Cloud Vector EngineDevelop a CAP-based (multitenant) application using GenAI and Retrieval Augmented GenerationRead about other partner use cases leveraging SAP BTP’s Generative AI capabilitiesSAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 1]SAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 2]SAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 3]
Introduction:In continuing the exploration of innovative SAP HANA Cloud vector engine implementations, we now turn to another remarkable example from LeverX. LeverX from SAP Partner Ecosystem has developed an innovative solution as part of the SAP BTP Gen AI Lighthouse Program. Continuing from Wipro and Deloitte’s success stories, this blog explores how LeverX leverages the SAP HANA Cloud vector engine to transform operations and boost efficiency across industries. LeverX has implemented the Unstructured Data Intelligent Assistant solution, addressing challenges in searching and analyzing unstructured data stored in custom formats, helping companies streamline and optimize production design processes.Use Case: Unstructured Data Intelligent AssistantProblem Statement:Most companies face challenges in effectively searching, navigating, and analyzing unstructured or custom data stored in various formats such as CAD and PDX. They struggle with the lack of embedded tools for searching through local custom repositories and cloud data storage containing unstructured or packed data. Additionally, data management issues, such as the creation of duplicated data instead of reusing existing templates, further complicate the process. Complex tools make it harder for users to use natural language prompts for efficient data search and analysis across both SAP and non-SAP platforms.Solution:LeverX designed an Unstructured Data Intelligent Assistant solution on the SAP BTP platform that, according to the company, seamlessly integrates ERP data sources, utilizing efficient data preparation methods and harnessing the SAP HANA Cloud vector engine for advanced storage and vector-based search capabilities. It leverages SAP BTP’s request processing layer, utilizing the SAP Generative AI Hub to transform natural language prompts into SQL queries and performs vector search against vectorized information in HANA Cloud, enabling efficient and accurate data retrieval. The processed data is then visualized and made accessible through a flexible Intelligent Assistant component.The Intelligent Assistant operates in two modes: Standalone Mode and Embedded Mode. In Standalone Mode, it functions independently, providing powerful search and analysis capabilities through APIs, allowing users to interact with unstructured data across various platforms. In Embedded Mode, it integrates seamlessly within SAP systems, enhancing the ability to search and analyze unstructured data directly within the SAP environment.This dual-mode functionality ensures that the Intelligent Assistant can be integrated across different workflows and systems, whether on SAP or non-SAP platforms. By supporting both standalone and embedded deployment, this solution addresses the lack of ready-to-go tools in the market, significantly reducing the effort required to search through files in proprietary formats.LeverX created the solution to help non-technical users analyze proprietary data more effectively, support better data management practices, and reduce duplication through the reuse of existing templates to enhance operational efficiency and decision-making processes.Solution Overview:Reference Architecture: Value Add of SAP HANA Cloud vector engine:The SAP HANA Cloud Vector Engine plays a crucial role in the Intelligent Assistant solution by enhancing the capabilities of searching and analyzing unstructured data. Here’s how it is used in this context:Vector-Based Search Capabilities: The SAP HANA Cloud vector engine powers similarity searches by interpreting the semantic meaning of queries, making it more effective in retrieving relevant information from unstructured data like PDFs, CAD files, and PDX files, compared to traditional keyword searches.Handling Unstructured Data: Unstructured data often lacks a predefined schema, making it challenging to search and analyze using conventional methods. The vector engine addresses this challenge by supporting the storage and querying of vectors (obtained from embedding the unstructured data) that capture the context and relationships, enabling accurate and efficient searches even with large and varied datasets.Enhanced Data Retrieval: The vector similarity search capability allows the Intelligent Assistant to find data based on conceptual similarity rather than exact matches, making searches with natural language prompts more intuitive and user-friendly.Integration with Natural Language Processing: The vector engine works in conjunction with the SAP generative AI hub, which processes natural language queries into SQL and performs vector search against vectorized information in HANA Cloud. The vector engine performs the search and retrieval process, allowing users to ask complex questions in plain language. It provides precise answers, even when the underlying data is unstructured and distributed across different repositories.Integration Across SAP and Non-SAP Systems: The vector engine’s integration with SAP BTP allows for seamless access and retrieval of data across both SAP and non-SAP systems, ensuring comprehensive search capabilities across all relevant data sources.Conclusion:Our partners, such as Wipro, Deloitte, and LeverX, are leveraging the SAP HANA Cloud vector engine and SAP BTP services to create innovative solutions that drive real value for our joint customers across various industries. These collaborations showcase how the power of SAP technologies is transforming business operations and enabling new levels of efficiency and insight. From enhancing AI-driven solutions to improving data management and analytics, each partner’s use case has showcased the transformative potential of using SAP HANA Cloud to power intelligent data applications. With the insights shared in this series, I hope to have provided a comprehensive understanding of how SAP HANA Cloud can be leveraged to solve real-world challenges. Keep an eye out for future events as we keep exploring the exciting and ever-changing world of technology powered by the in-memory database.Note: This blog is a collaborative effort between SAP HANA Cloud Product Management and LeverX, highlighting the innovative solution developed by the LeverX team: Vitali Usau (vitali.usau@leverx.com), Dzmtry Buriak (dzmitry.buriak@leverx.com), Pavel Lazhbanau (pavel.lazhbanau@leverx.com), Siarhei Valenda (siarhei.valenda@leverx.com). For those interested in learning more or exploring implementation details, please feel free to reach out to the mentioned team member contacts.References:Try for yourself:Explore SAP HANA Cloud Vector Engine via Basic TrialHarnessing Generative AI Capabilities with SAP HANA Cloud Vector EngineDevelop a CAP-based (multitenant) application using GenAI and Retrieval Augmented GenerationRead about other partner use cases leveraging SAP BTP’s Generative AI capabilitiesSAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 1]SAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 2]SAP Lighthouse Program – Partner Use Cases adopting BTP GenAI Capabilities [Part 3] Read More Technology Blogs by SAP articles
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