The Award honors an organization that has successfully integrated data and AI into its core business processes, driving significant innovation and refining both organizational and product value. This award recognizes a visionary project that has transformed strategy into action by leveraging data and AI to enhance business operations, optimize decision-making, and create new growth opportunities. The winning organization should demonstrate how it has effectively infused these technologies across various aspects of the business, leading to measurable improvements in efficiency, customer experience, and market positioning. This award highlights the journey from vision to implementation, showcasing the organization’s commitment to embracing data and AI for long-term success.
About Volvo Penta: At Volvo Penta, we aim to be the most forward thinking and customer-focused supplier of sustainable power solutions. We develop, manufacture and market world-leading engines and complete power systems for boats and industrial applications. With customers in over 130 countries around the world, we work to build close partnerships, leveraging our industrial and marine engineering expertise to deliver innovative solutions for use on land and at sea. We are a part of the Volvo Group which includes Volvo Trucks, Renault Trucks, Volvo Construction Equipment, Volvo Buses among others.
The focus in 2023 into 2024 has been to
advertise the Data & AI Strategy as well as to hands-on work with the business to integrate the data goals into their business goals
initiate execution of the strategy on low hanging pain points to build a cache of success stories
showcase a clear red thread of 1 business goal or pain point being resolved through the help of Data & Analytics
The above point 3 is easier said than done since high level business goals are complex and are supported by multiple functions and underlying goals that jointly ensure success. Thus, among the top 4 business goals for Volvo Penta (Business Growth, Customer Success, People and Sustainability) we chose Sustainability as the area to deep dive and focus on.
Sustainability as an area is a green field, with concrete key results and relatively straightforward. Volvo Penta’s top goal within Sustainability is -40% reduction in CO2 emissions. Sudharshan worked together with the other Heads of Data within the Volvo Group to break down the top level Sustainability core business goals into components where Data & Analytics can support.
This has led to extremely positive buy-in from all the Heads of Sustainability within the Volvo Group and focused implementation of various D&A activities (data quality, governance, data engineering). The various areas within Data (Data Governance & Management, Information Architecture, Data Products, Data Literacy, APIs) are also harmonized and working together towards a common business goal. We have seen very good results in holistically working with all areas of Data for a given use case area which also lead to easier adoption by our business as well as manageable workload on the company.
Scania is a world leading provider of transport solutions with more than 58,000 employees in more than 100 countries. Together with our partners and customers we are driving the shift towards a sustainable transport system by: 1. Developing and offering premium products, services and solutions for sustainable transport For more than 130 years, our core business has been to develop and offer premium products, services and solutions for our customers, and to continuously improve fuel efficiency and uptime. As we drive the shift to sustainable transport, this continues to be at the heart of our approach. We offer products and services designed to support our customers’ transition to a sustainable transport future. These include electric vehicles and charging solutions, as well as solutions based on renewable fuels. Every solution is tailored to customer requirements and local circumstances. 2. Partnering up to create the enabling conditions for sustainable transport Sustainable transport depends on the right conditions to flourish. We work with partners across the transport ecosystem to develop sustainable infrastructure and resources, and push for the policies and investments needed to make sustainable transport a reality. We are pioneers in supply chain sustainability, forging groundbreaking partnerships with suppliers to rapidly decarbonise the transport industry’s supply chain. 3. Exploring and accelerating the development of tomorrow’s transport system By pushing the boundaries of what’s possible today, we are shaping the transport system of tomorrow. We do this by investing in R&D, backing start-ups and harnessing new ideas, technologies and business models that lie outside our current core. 4. Managing our impacts on people and planet We lead by example, managing our social and environmental impacts where they are biggest throughout our value chain. We focus on three sustainability priorities: people sustainability, decarbonisation and circularity.
At the heart of every successful company lies a simple truth: data is more than just numbers, it’s the lifeblood of relationships, decisions, and growth. For Scania, the QING Master Data Management (MDM) Customer Program is the key to unlocking that potential. This project wasn’t just about improving systems; it was about uniting people, changing the mindset, encouraging collaboration, and building a shared foundation of trust in the data that supports Scania’s global operations. The QING MDM Customer Program was launched with a bold vision to consolidate all of Scania’s customer data into one cohesive and reliable solution. This meant creating a “single source of truth” that would simplify decision-making, improve efficiency, and support both current and future Business and IT needs. It also meant something much more: it meant empowering every person at Scania to do their job better, to feel confident in the data they use, and to know that they are contributing to something bigger than just a work task. For over eight years, Robert Ciborowski, the QING MDM Solution Manager, and Yasmine Mohamed, IT MDM Strategist, have been at the helm of this remarkable journey. Their leadership is more than leading a technical project; it’s driven by a shared passion for making Scania stronger, more agile, more data-driven, and more connected. Together, they helped transform how Scania manages its customer information, creating a robust solution that not only supports the business but also uplifts the people working within it.
Strategic Objectives: Empowering People Through Data The QING MDM program was built on the belief that good data has the power to change everything. By centralizing customer information, Scania can make faster, more informed decisions, adapt to changing markets, and ensure that reliable data always supports its people. The program’s key goals reflect this commitment to both innovation and human impact: 1. Supporting Business and IT Teams: By creating a single source of truth for customer data, the QING program not only helps streamline operations but also gives Scania’s teams the confidence they need to adapt quickly to new challenges and opportunities. 2. Responding to Changing Needs: With centralized data, Scania can now pivot faster to meet the demands of a rapidly changing market. This agility allows the company to stay competitive, while reducing stress for employees by providing them with the right tools and information when they need it most. 3. Cutting Costs and Saving Time: The program eliminates redundant systems, freeing up time and resources so that people can focus on what matters most—innovating, growing, and building stronger customer relationships. 4. Unlocking Insight with Advanced Analytics: By integrating customer data into Scania’s Data Lake and data mesh the program empowers teams with deeper insights, helping them make data-driven decisions that benefit not just the company, but the customers and communities they serve. 5. Ensuring Compliance and Trust: In an age where privacy and data security are more important than ever, the QING MDM program gives Scania the tools to meet global regulations like GDPR. This isn’t just about ticking boxes; it’s about ensuring that everyone interacting with Scania employees, partners, and customers can trust that their data is being handled responsibly. 6. Building the Future with a Modern Data Strategy: Scania’s commitment to innovation doesn’t stop at today’s challenges. The QING program lays the groundwork for a future where data is more than just a resource, it’s a shared asset that drives long-term value for everyone involved. Key Challenges and Opportunities: Standing strong and growing together through every challenge Every transformational journey comes with its share of challenges. For the QING MDM program, these challenges weren’t just obstacles they were opportunities to strengthen
Scania’s culture of collaboration and innovation. 1. Global Data Quality and Duplication: Scania’s global reach meant managing data from different systems and regions. The challenge of ensuring data consistency and eliminating duplication across borders was immense but it was also a chance to unite Scania’s global teams around a common goal. 2. Overcoming Resource Limitations: Like any large-scale project, the QING MDM program faced resource constraints. Instead of seeing this as a limitation, the team adopted new technologies, worked smarter and demonstrated how resilience and creativity can overcome even the toughest challenges. 3. Building Global Cooperation: As a 24/7 operation, Scania needed a solution that could handle the need for constant data updates across different time zones. This challenge pushed the team to develop a system that works around the clock and strengthens collaboration between international teams. 4. Engaging Stakeholders, Uniting Visions: Keeping stakeholders aligned wasn’t always easy, but the program’s collaborative approach helped bridge gaps, ensuring that everyone was invested in its success. Innovative Solutions: A People-First Approach to Innovation Innovation is about more than just technology, it’s about understanding the people behind the data and creating solutions that empower them and using the innovative technology for a real- life business case.
The QING MDM Program embraced this philosophy with every decision it made: 1. Focused on Real Business Value: Most MDM implementations start with setting up the Governance farmwork, which usually takes a very long time and hence delays the ROI of the MDM solution. However, for QING, the team never lost sight of what really matters, delivering tangible business benefits across Scania. By focusing on use cases that brought immediate, measurable value, they ensured that the program’s success was noticed across the organization and reversed the traditional way of MDM implementation. 2. Leveraging New Technologies for Human Benefit: As mentioned the limitation of the number of resources was a constraint however; by embracing technologies like Bots, Data Integration, and Data Processing systems, QING team overcame this obstacle. The QING MDM program didn’t just detect and solve technical problems, it made life easier for the people who rely on data daily. 3. A Cloud-First, Buy-First Strategy: Instead of reinventing the wheel, the team opted for a buy-first, cloud-first approach, ensuring scalability, flexibility, and security. This strategy not only supported Scania’s global needs but also freed up resources to focus on what really matters and helping people succeed. 4. Enriching Data, Enhancing Customer Experience: As one of the main constraints was improving data quality, integrating external data sources created the opportunity to enrich Scania’s customer insights. While complex, this enriched data helped Scania build stronger, more meaningful connections with the customers and all of this was done without any Data Stewards. 5. A True Collaboration Between IT and Business: One of the program’s greatest innovations was its commitment to balance. By adopting a 50/50 investment between business and IT, the program created a culture of shared ownership, where everyone worked together to overcome challenges and drive real, lasting value. Positive Impact on the Nordic DAIR Community: Leading by Example
The QING MDM Program has transformed Scania into a data-driven company and aided its digitalization journey. Over the past two years, the QING Team haven’t missed any opportunity to share their knowledge to inspire the entire (DAIR) community, by presenting real-life stories from QING implementations and MVPs. Meanwhile, discussing with peers from the various Nordic industries the new standards for data governance, collaboration, and innovation, the program serves as a blueprint for how organizations can leverage data to create real, meaningful value. 1. Setting New Standards for Data Governance (Reversed Governance): The QING MDM program has demonstrated how large-scale organizations can manage data quality and compliance with minor human touch ensuring both accuracy and trust, especially in regions with strict data privacy regulations. 2. Pioneering a Modern Data Strategy: Scania’s forward-thinking approach to data isn’t just about technology, it’s about creating a culture where data is seen as a shared asset that benefits everyone. This approach offers valuable insights for the Nordic DAIR community as businesses across the region look to harness the power of data. 3. Inspiring Collaboration and Innovation: The program’s success wasn’t built in isolation, it was the result of true collaboration between people, teams, and technologies. This collaborative spirit is a powerful reminder of what’s possible when we work together toward a common goal. 4. Transforming Operations and Decision-Making: With data at the heart of every decision, Scania is becoming a leader in data-driven operations. The lessons learned from this journey offer invaluable insights for other organizations looking to unlock the full potential of their data.
At its core, the QING MDM Customer Program is a story about vision and people. It’s about building trust, encouraging collaboration, and empowering everyone at Scania to thrive in a data-driven world. Through innovation, resilience, and a commitment to shared success, the program has transformed not just how Scania manages data, but how it views its future and how to embrace the opportunities. In a world where data can make or break success, QING MDM is helping Scania unlock a future where people, teams, and businesses are empowered to achieve more, together.
KBLab is a research and development laboratory at the National Library of Sweden. Its primary focus is on the AI-elevated accessibility to the library’s digital collections and on the creation of accessible, transparent, and robust language models. The lab engages in projects that leverage the library’s extensive collections of digital resources to develop tools and technologies for Swedish language processing. One of its central goals is to support both researchers and the public in accessing and analyzing large-scale text data in ways that are reliable and open.
KBLab is taking a two-pronged approach in training transformer models, tailoring each trajectory to meet the distinct needs of linguistic research and the Swedish language.
Trajectory 1: Predictive Models with Curated Data
The first trajectory focuses on creating predictive models that are trained on highly curated, meticulously assembled datasets drawn from the library’s vast collections. This approach emphasizes data precision and relevance, enabling models to be highly accurate and effective in predictive tasks. The data is selected and prepared with a high degree of scrutiny, ensuring that it is well-structured and relevant to specific predictive goals. Such rigorous curation allows these models to excel in tasks like text classification, document analysis, and other applications requiring robust, domain-specific predictions.
Trajectory 2: Fine-Tuning Multilingual LLMs for Swedish
The second trajectory is geared toward fine-tuning large multilingual models (LLMs) and foundational models, aiming to enhance their functionality and fluency in the Swedish language. By training these models with language-specific data and fine-tuning their parameters, KBLab aims to advance the capacity of these foundational models to understand, generate, and translate Swedish with greater precision and cultural nuance.
The first trajectory reflects a commitment to extracting refined insights from carefully chosen subsets of data, making it ideal for tasks that benefit from high fidelity and interpretability in Swedish. KBLab’s predictive models are released openly and have been downloaded more than four millions times from Huggingface.
The second trajectory leverages transfer learning and adaptation techniques, allowing multilingual models to achieve superior performance in Swedish-specific tasks without the need to build from scratch. Such advancements improve the models’ applications in natural language understanding, conversational AI, and document generation for Swedish, ultimately contributing to a more robust digital infrastructure for Swedish language processing.
Through these dual pathways, KBLab is not only advancing predictive capabilities rooted in Swedish literature and archival data but also enhancing multilingual models to better accommodate and serve Swedish language needs in diverse applications.
Additional Links
https://huggingface.co/KBLab
The focus in 2023 into 2024 has been to
advertise the Data & AI Strategy as well as to hands-on work with the business to integrate the data goals into their business goals
initiate execution of the strategy on low hanging pain points to build a cache of success stories
showcase a clear red thread of 1 business goal or pain point being resolved through the help of Data & Analytics
The above point 3 is easier said than done since high level business goals are complex and are supported by multiple functions and underlying goals that jointly ensure success. Thus, among the top 4 business goals for Volvo Penta (Business Growth, Customer Success, People and Sustainability) we chose Sustainability as the area to deep dive and focus on.
Sustainability as an area is a green field, with concrete key results and relatively straightforward. Volvo Penta’s top goal within Sustainability is -40% reduction in CO2 emissions. Sudharshan worked together with the other Heads of Data within the Volvo Group to break down the top level Sustainability core business goals into components where Data & Analytics can support.
This has led to extremely positive buy-in from all the Heads of Sustainability within the Volvo Group and focused implementation of various D&A activities (data quality, governance, data engineering). The various areas within Data (Data Governance & Management, Information Architecture, Data Products, Data Literacy, APIs) are also harmonized and working together towards a common business goal. We have seen very good results in holistically working with all areas of Data for a given use case area which also lead to easier adoption by our business as well as manageable workload on the company.
SvenAI, developed by Tyréns AB, is an advanced AI-driven knowledge management platform tailored to meet the rigorous demands of infrastructure and urban planning. This proprietary solution is built to ensure data privacy, enable secure data retrieval, and provide contextually rich insights. Unlike standard AI models, SvenAI integrates Retrieval-Augmented Generation (RAG), Hypothetical Document Embeddings (HyDE), LLM ReRank, and a unique Graph RAG inspired by Microsoft’s “global to local” research. These technologies work together to deliver both broad and detailed responses by navigating relationships within a structured knowledge graph. Key features such as Drag, Drop, Retrain, Collections, Workspaces, and Function Calling empower Tyréns’ team to customize the knowledge base and ensure that SvenAI continuously evolves with user input. This platform has become indispensable for efficient decision-making across complex projects, setting a new standard for secure, AI-driven knowledge management.
Scope of the Project
The SvenAI project aimed to create a secure, adaptable, and precise knowledge management system tailored specifically for the infrastructure and urban planning sectors. Tyréns, an industry leader in these areas, required a solution that could handle complex, context-heavy queries, maintain strict data privacy, and foster collaboration. Recognizing the limitations and risks associated with third-party AI services, Tyréns chose to develop an in-house system that could safeguard proprietary data while leveraging the latest advancements in AI.
Solution
SvenAI combines cutting-edge AI methodologies with user-centric features, creating a powerful, flexible platform:
Advanced AI Techniques: SvenAI incorporates Retrieval-Augmented Generation (RAG), HyDE, and LLM ReRank to deliver accurate, context-aware responses. Graph RAG, based on Microsoft’s “global to local” research, allows SvenAI to structure data into a knowledge graph and navigate complex relationships, providing nuanced answers that typical AI models cannot achieve.
User-Driven Customization: Features like Drag, Drop, Retrain allow users to upload documents and retrain the model to incorporate new knowledge. Customizable Collections and Workspaces let users create project-specific knowledge sets, while Function Calling and Agents enable SvenAI to dynamically respond to diverse query types.
Collaborative Knowledge Hub: File Upload and Commit to Knowledge Structure empower all team members to contribute to the knowledge base, ensuring it stays relevant and comprehensive.
Positive Impact
SvenAI has transformed knowledge management at Tyréns by providing a secure, efficient platform for information retrieval and collaboration. The system’s dual-layered Graph RAG, advanced retrieval techniques, and user-driven customization have streamlined workflows and enhanced decision-making in critical infrastructure and urban planning projects. SvenAI’s modular and adaptable architecture not only reduces reliance on external providers but also adds value by continuously evolving with user input, ensuring it remains a valuable asset across the organization.
SvenAI deserves recognition for its groundbreaking approach to AI-driven knowledge management in the infrastructure and urban planning sectors—a field known for its conservative, risk-averse approach to technology adoption. Infrastructure projects typically involve high stakes, where decisions have long-term financial, social, and environmental impacts. Despite operating in a sector that traditionally avoids innovation due to risk aversion, Tyréns not only built SvenAI to meet stringent internal requirements but also created a solution that outperforms standard offerings across multiple domains.
What makes SvenAI truly remarkable is that it doesn’t just serve Tyréns’ needs. Tyréns has taken the unprecedented step of offering SvenAI as a Software-as-a-Service (SaaS) solution, making this sophisticated, privacy-focused knowledge management system available to other players in the industry, including competitors. By doing so, Tyréns demonstrates a commitment to advancing the entire sector, setting a new standard for AI in infrastructure and urban planning. This move towards openness and collaboration is a bold statement in a traditionally closed industry, showcasing SvenAI’s potential to transform knowledge management across the field.
SvenAI’s innovative approach to balancing data privacy with advanced AI capabilities, along with Tyréns’ willingness to share the platform with others, positions it as a unique solution in a high-stakes industry. It has not only elevated Tyréns’ competitive edge but also established a new benchmark for responsible AI use in sensitive, high-impact sectors. This combination of sector-leading technology, willingness to share expertise, and commitment to advancing industry standards make SvenAI a worthy recipient of this award.
Project Background
Tyréns AB, a leader in the architecture, engineering, and infrastructure sectors, initiated the SvenAI project with support from Predli to address critical data privacy and operational needs. The organization recognized the limitations of mainstream AI platforms, which posed potential risks to sensitive data and lacked the precision required for the intricate, context-heavy queries in infrastructure and urban planning. The goal was to create a proprietary, in-house AI solution that could deliver secure, accurate insights tailored to the specific demands of these fields.
Overview
SvenAI is a comprehensive knowledge management system that integrates multiple advanced AI methodologies, including Retrieval-Augmented Generation (RAG), Hypothetical Document Embeddings (HyDE), LLM ReRank, and a Graph RAG inspired by Microsoft’s “global to local” research. This evolved Graph RAG allows SvenAI to structure data into a knowledge graph, enabling it to navigate complex relationships and provide contextually relevant answers. Key features like Drag, Drop, Retrain, Collections, Workspaces, and Function Calling empower users to continuously expand and refine the knowledge base, ensuring SvenAI’s outputs remain highly relevant and accurate.
Strategic Objectives
The primary objectives of SvenAI were:
Data Privacy and Control: Protect proprietary data and reduce dependency on external AI services, ensuring all sensitive information remains within Tyréns’ secure infrastructure.
Efficient, Data-Driven Decision-Making: Enable quick, precise responses to complex, context-sensitive queries, supporting decision-making in high-stakes infrastructure projects.
User Empowerment and Collaboration: Foster a collaborative environment where users can contribute to and customize the knowledge base, creating project-specific resources for enhanced relevance and accuracy.
Key Challenges
Data Privacy and Security: Relying on third-party AI platforms posed potential risks of data leakage, compromising Tyréns’ competitive edge in the industry.
Handling Complex Queries: Infrastructure and urban planning projects involve highly specialized, context-sensitive questions, which standard AI retrieval models are not equipped to handle effectively.
Innovative Solution
Graph RAG’s Dual Search Strategy: Based on Microsoft’s “global to local” research, Graph RAG combines global and local search strategies within a structured knowledge graph. This approach allows SvenAI to provide comprehensive, contextually rich responses, ideal for the complex, layered queries encountered in infrastructure projects.
HyDE and LLM ReRank: These techniques generate hypothetical documents and re-rank results based on query relevance, ensuring that SvenAI delivers accurate answers even when direct information is sparse.
User-Centric Enhancements: Drag, Drop, Retrain enables users to upload and incorporate new data; Collections and Workspaces allow for project-specific customization; Function Calling and Agents adapt responses dynamically for diverse query types, enhancing SvenAI’s flexibility.
Positive Impact
SvenAI has revolutionized Tyréns’ knowledge management, providing a secure, user-driven platform that simplifies information retrieval and enhances collaboration. By allowing users to contribute to and refine the knowledge base, SvenAI continuously adapts to new information and project-specific needs, supporting better decision-making across high-stakes infrastructure and urban planning initiatives. The platform’s unique Graph RAG approach further ensures that SvenAI can handle complex, multi-faceted queries with precision, giving Tyréns a significant edge in a competitive, risk-averse industry.
Value Added Output in 2024
Throughout 2024, SvenAI has proven invaluable by delivering measurable benefits across Tyréns’ projects:
Enhanced Efficiency: By reducing reliance on external AI providers, SvenAI has streamlined knowledge management workflows, saving time and resources.
Improved Decision-Making: With Graph RAG and other retrieval techniques, SvenAI provides contextually rich answers that directly contribute to higher-quality decision-making.
Collaborative Growth: The platform’s user-driven features have fostered a collaborative knowledge-sharing culture within Tyréns, while its SaaS model has allowed external organizations to benefit from SvenAI’s capabilities, promoting growth and innovation across the sector.
SvenAI’s contributions in 2024 highlight its status as a transformative tool in knowledge management, setting a new standard for secure, user-centric, AI-driven solutions in infrastructure
Building Our Own Knowledge System: Why We Took This Path
https://www.linkedin.com/pulse/building-our-own-knowledge-system-why-we-took-path-stefan-wendin-hxaif/