Meet the innovators using data and AI to reshape industries, solve problems and set a new bar for what's possible with Databricks.
by Sara Steffen
The 2026 Databricks Customer Awards recognize organizations and leaders who are using the Databricks Platform to solve hard problems and deliver results that matter, from ingesting 10 trillion rows of data a year to helping match medical volunteers to underserved communities across the globe.
This year's Named Awards winners span 8 categories and 4 regions, representing industries as varied as semiconductors, clean energy, dairy farming, telecommunications and enterprise software. What they share is a belief that data and AI can change how an industry operates.
Meet the winners.
Applied Materials is a leading semiconductor and materials engineering company that designs and manufactures the equipment used to make virtually every new chip in the world. Behind that equipment sits an equally critical asset: a vast estate of engineering, manufacturing, supply chain and finance data that the company has long brought together in a central data lake.
The original lake, built on Hadoop, did its job — it consolidated the data. But the demands had changed: AI workloads, real-time analytics, governed self-service and use cases the original architecture was never designed for required a new approach. Applied Materials uses the Databricks Platform to modernize that foundation — moving from a storage-and-batch data lake to a lakehouse where governance, analytics and AI live together. The shift was less about consolidating data than about unlocking what could ultimately be done with it.
Less than a year post go-live, the platform delivered:
What started as a platform modernization has become more of a way of working. AI now sits alongside the people who design the machines that make the world's chips — not as a tool they pick up occasionally, but as a day-to-day collaborator. Data runs through the full lifecycle of how Applied Materials operates, from insight to action, making "data-driven" less a slogan than the default mode of innovating, optimizing and deciding.
Virgin Atlantic was founded by entrepreneur Sir Richard Branson in 1984, with innovation and amazing customer service at its core. Headquartered in London, the airline operates flights to 28 destinations year-round. Alongside its shareholder and partner, Delta Air Lines, Virgin Atlantic operates a leading transatlantic network with onward connections to over 200 cities worldwide.
Virgin Atlantic brings together customer, commercial, financial and operational data that previously sat in separate systems. It uses the Databricks Platform as an integrated, enterprise‑scale decision environment, connecting these domains on a unified, governed foundation so teams can work from shared data rather than isolated reports.
On this foundation, Virgin Atlantic:
Taken together, this approach turns data into an end‑to‑end story rather than a set of disconnected projects. Virgin Atlantic treats being data‑driven as a way of running the airline, using a unified platform so insights flow across functions and support more timely, coordinated decisions for both customers and operations.
Fonterra Co-operative Group is one of the largest dairy cooperatives in the world, owned by thousands of New Zealand farmer shareholders and supplying natural dairy to customers globally. Data and AI help Fonterra gain the insights it needs to run complex operations around financial planning and supply chain decisions more efficiently across its global network.
Historically, Fonterra relied on several legacy analytics platforms that could create complexity, duplication and delays for business users. After migrating to Databricks, they centralized Fonterra data in a governed lakehouse, reducing manual data movement and enabling teams to turn data into decisions faster and more reliably.
On this foundation, Fonterra:
Fonterra treats AI as a collaborator that helps teams with proactive, insight-led decision-making.
Vivo, Telefónica’s Brazil trademark, is the leading telecommunications company in Brazil, delivering mobile and fixed-line connectivity, broadband internet and TV services to consumers, businesses and public-sector organizations across the country. The company also provides digital services across different areas, including entertainment, sports, digital security, financial services and health. Using data and AI, Vivo is gaining the insights needed to run complex network operations and customer experiences more efficiently.
Vivo relied on a mix of legacy data warehouses and analytics tools, which added complexity, cost and latency to critical reporting and experimentation. As they evaluate and expand their use of Databricks, the team is consolidating data into a governed lakehouse, reducing pipeline duplication and giving business and technical teams a more scalable, fast and reliable foundation for analytics and AI.
On this foundation, Vivo:
Across these initiatives, Vivo positions AI as a strategic collaborator, strengthening its ability to deliver resilient connectivity and elevate digital experiences for millions of Brazilians.
Virtue Foundation is a global nonprofit organization focused on improving access to healthcare in underserved regions by connecting clinicians, hospitals and humanitarian organizations to where care is needed most. The organization uses data and AI to understand global health gaps better and coordinate medical volunteer efforts at scale.
Virtue Foundation brings together fragmented global hospital and non-government organization (NGO) data that is often inconsistent, incomplete or difficult to maintain. To address this, the organization built a data pipeline that powers VFMatch.org, helping unify and structure global health information into a usable foundation for decision-making and coordination.
On this foundation, Virtue Foundation:
These capabilities support the Virtue Foundation, which has helped serve more than 50,000 patients, supported thousands of surgical cases and enabled the matching of hundreds of volunteers and nonprofit partners worldwide.
These efforts demonstrate how Virtue Foundation is using data and AI to strengthen global health coordination and improve access to care in underserved communities.
Octopus Energy is a global clean energy and technology company with operations spanning 27 countries. As the UK’s largest energy provider, Octopus is on a mission to accelerate the energy transition to benefit both people and the planet. By transforming over 460,000 passive EVs and smart assets into over 3GW of shiftable capacity, the company has created the world’s largest Virtual Power Plant (larger than the UK’s largest gas plant) capable of balancing the grid during peak demand.
Databricks allows Octopus to consolidate data from disparate regions and products into a single unified platform. Now the company can ingest more than 10 trillion rows of data per year while thousands of people across the business collaborate and experiment safely — reducing friction in both day-to-day analytics and large-scale innovation.
On this foundation, Octopus Energy:
Across these efforts, Octopus Energy treats AI as a strategic collaborator in its mission to build a fairer, greener grid — using data to deliver lower bills, cleaner power and better experiences for 11 million customers.
Axpo is Switzerland’s largest producer of electricity, an international leader in energy trading and a leader in the marketing of solar and wind power. To improve how employees access and use complex technical and commercial information, Axpo has built a set of AI-driven applications using Databricks infrastructure and Agent Bricks.
At its core is AxploreAI, a central GenAI multi-agent platform, designed to become the one place to know everything at Axpo, always based on each user’s access rights. It connects employees to information across engineering data, trading knowledge, internal processes and corporate documentation such as IT and HR content.
Built on an API-first architecture with RAG, Vector Search and OCR, AxploreAI brings together more than 60 internal data sources into a secure and searchable intelligence layer, integrated in the digital touchpoints employees rely on every day. Its RAG pipeline is tailored to the content and format of each source, can process multiple file types and preserves original access controls, making enterprise knowledge instantly accessible without compromising governance.
Alongside its knowledge platform, Axpo is also applying AI to improve data quality and efficiency in procurement-related processes. In a complex operating environment shaped by fragmented systems, multiple legal entities and inconsistent free-text data, Axpo developed an AI-based classifier within its Databricks data lake to bring greater structure and consistency to spend data. Operating at around 90% average precision, the solution analyses invoice descriptions with supplier information across multiple languages, helping automate classification, reduce manual effort and continuously improve the quality of procurement data over time.
On this foundation, Axpo is scaling AI directly into its core business processes:
Together, these initiatives show how Axpo is embedding AI directly into everyday work across a highly complex energy business, transforming how teams access information, classify data and make decisions.
Atlassian is a global software company that builds collaboration, development and productivity tools used by teams worldwide. The company is transforming its security operations by rethinking how it collects, stores and analyzes security telemetry at scale.
After reaching petabyte-scale security data volumes, Atlassian identified limitations in its legacy SIEM that prevented it from operating at that scale. The company launched “Project Banyan” to build a modern Security Lakehouse on the Databricks Platform. The goal was to create an open, governed foundation that could support long-horizon threat hunting, advanced analytics and faster incident response across billions of security events.
As part of this transformation, Atlassian standardized security data using the Open Cybersecurity Schema Framework (OCSF) and migrated detection logic to PySpark, reducing dependency on proprietary tooling and enabling more flexible, ML-driven anomaly detection.
On this foundation, Atlassian:
Atlassian is also a private preview partner for Lakewatch, helping shape future capabilities for direct-to-lakehouse ingestion. Together, these efforts show how Atlassian has transformed security operations into a scalable, governed and AI-enabled system that improves both speed and accessibility of insights across the organization.
Wassym Bensaid, Chief Software Officer of Rivian and Co-CEO and CTO of Rivian and Volkswagen Group Technologies is leading Rivian’s transformation into an AI-first company.
His team has driven the shift from software-defined vehicles to AI-defined vehicles, using data intelligence as the foundation for everything across Rivian’s vehicle and mobility platform — all the way to the daily drive experience using data intelligence as the foundation for everything across Rivian’s vehicle and mobility platform.
To enable this shift, Rivian modernized its data stack on the Databricks Platform, unifying vehicle, factory and enterprise data into a single foundation. Wassym and his team also consolidated legacy systems, including Snowflake and Redshift, into a unified Delta and Unity Catalog layer that establishes a common data and AI fabric across the organization.
On this foundation, Rivian:
As Rivian prepares for a 10x increase in vehicle data volume, Wassym and his team have designed Rivian’s data architecture to scale to 500–600 petabytes this year. Serverless ETL alone saves an estimated 400 engineering hours per month, enabling faster iteration without proportional headcount growth.
Wassym is now extending this foundation to the $5.8 billion Rivian and Volkswagen Group Technologies joint venture (RV Tech), where Rivian’s software and data infrastructure will support multiple Volkswagen Group brands — positioning Rivian as a global software and data platform provider.
Lippert is a global manufacturer of highly engineered components and systems for the RV, marine, automotive and housing industries. The company is using data and AI to enhance customer experience, streamline operations and support service delivery across its business units.
Kenan Colson, VP of Data and AI at Lippert, has played a central role in driving data intelligence adoption across the organization. Her efforts have focused on building internal alignment around AI initiatives and demonstrating measurable business value through production deployments spanning customer service, finance and HR.
Under her leadership, Lippert has transformed its Customer Care Center by deploying an AI-enabled Customer Care “Super-Agent” that can handle high call volumes. This initiative significantly accelerated employee onboarding.
Kenan also deployed AI capabilities in additional business functions with specialized “zero-touch” solutions, including:
Kenan also contributed to external thought-leadership by speaking at industry events and sharing insights on the use of data and AI in enterprise settings. Together, these efforts show how Kenan Colson is driving enterprise-wide adoption of AI at Lippert by turning early success into scaled, cross-functional impact across the organization.
Applied Materials, Virgin Atlantic, Fonterra, Vivo (Telefonica Brazil), Virtue Foundation, Octopus Energy, Axpo, Atlassian, Wassym Bensaid at Rivian and Volkswagen Group Technologies and Kenan Colson at Lippert.
Ten winners. Ten stories. One thing in common: a belief that data and AI can be a force for the better and the commitment to prove it. Their work inspires us, challenges us and makes us excited for what comes next.
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