List of Databricks Data Intelligence Platform Customers
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Since 2010, our global team of researchers has been studying Databricks Data Intelligence Platform customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Databricks Data Intelligence Platform for ML and Data Science Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Databricks Data Intelligence Platform for ML and Data Science Platforms include: Regeneron Pharmaceuticals, a United States based Life Sciences organisation with 15182 employees and revenues of $142.02 billion, Genesis Energy, a New Zealand based Utilities organisation with 1278 employees and revenues of $2.13 billion, Shell Tunisia, a Tunisia based Oil, Gas and Chemicals organisation with 150 employees and revenues of $200.0 million, Octopus Energy, a United Kingdom based Utilities organisation with 100 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using Databricks Data Intelligence Platform, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Genesis Energy | Utilities | 1278 | $2.1B | New Zealand | Databricks | Databricks Data Intelligence Platform | ML and Data Science Platforms | 2025 | n/a |
In 2025, Genesis Energy deployed the Databricks Data Intelligence Platform to modernise its data ecosystem and accelerate enterprise AI adoption. The Databricks Data Intelligence Platform, classified as ML and Data Science Platforms, was incorporated as a core element of Genesis Energy’s Gen35 technology program to support generation operations, wholesale and trading modernization, and customer-facing use cases.
The implementation emphasized platform-level capabilities and operational AI workloads rather than exploratory proofs of concept, with the Databricks Data Intelligence Platform hosting model training, feature stores, and reusable data pipelines to produce algorithms and data sets used by trading and asset management teams. A training academy was embedded as part of the Databricks environment to upskill staff, and the platform was used to operationalize AI agents and generative AI workflows across multiple functional domains.
Integrations and operational coverage were explicitly enterprise wide, with the Databricks deployment working alongside an OpenAI ChatGPT for enterprise rollout and other major IT programs such as the Workday ERP and billing and CRM migrations mentioned in Genesis’ program portfolio. Operational use cases surfaced include AI on top of standard operating procedures and operational metrics to help engineers prioritise generation asset work, a People Pal agent for employee policy questions, and AI-assisted account management support for customer meetings.
Governance and delivery discipline were central to the rollout, Genesis Energy eschewed proof of concepts in favor of a streamlined business casing process that uses a one page template and a minimum 15 percent per annum ROI hurdle to progress ideas. Outcomes reported in the deployment include early production use cases delivering substantial efficiency, for example a cited circa 50 percent reduction in effort on some generation asset work, while ChatGPT for enterprise was rolled out to more than 80 percent of the organisation as part of the same data and AI pillar.
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Octopus Energy | Utilities | 100 | $10M | United Kingdom | Databricks | Databricks Data Intelligence Platform | ML and Data Science Platforms | 2021 | n/a |
In 2021, Octopus Energy adopted the Databricks Data Intelligence Platform. Kraken, the Octopus Energy Group platform, used Databricks to scale global data operations and Delta Sharing, cutting data processing costs by ~8x and reducing data load times from three days to eight hours.
The Databricks Data Intelligence Platform deployment centralized data engineering and analytics workloads for customer and operations analytics across Octopus businesses in the United Kingdom and international markets. The implementation emphasized Delta Lake data structures and Delta Sharing for governed distribution of curated datasets to downstream analytics consumers.
Functional capabilities implemented include data engineering pipelines, curated Delta Lake datasets, collaborative analytics workspaces and machine learning enabled model development consistent with ML and Data Science Platforms. The environment standardized batch and incremental processing to compress multi day loads into an eight hour operational window.
Operational coverage ran across Kraken teams supporting customer and operations analytics, with governance centered on shared Delta datasets and controlled data sharing to internal business units and international affiliates. Outcomes reported in the Databricks Kraken customer story include the ~8x reduction in processing costs and the decrease in data load time from three days to eight hours.
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Regeneron Pharmaceuticals | Life Sciences | 15182 | $142.0B | United States | Databricks | Databricks Data Intelligence Platform | ML and Data Science Platforms | 2018 | n/a |
In 2018, Regeneron Pharmaceuticals implemented the Databricks Data Intelligence Platform to unify and analyze petabytes of genomic and clinical data, positioning the deployment within the ML and Data Science Platforms category. The implementation is hosted on AWS in the United States and supports R&D and genomics workflows that feed drug discovery research.
The Databricks Data Intelligence Platform was configured to centralize high volume data ingestion and to accelerate data engineering and ETL pipelines, while providing interactive analytics and model development capabilities common to ML and Data Science Platforms. Implementation emphasis included scalable query performance for large genomic datasets and orchestration of ETL workloads to improve pipeline throughput.
Operational coverage focused on research and development functions in genomics, unifying clinical and sequencing data repositories for cross functional analysis. The deployment on AWS enabled elastic compute for large scale queries and batch ETL, and the solution is described in Databricks healthcare customer case materials that document the R&D use case.
Governance and workflow changes were oriented around centralized data access for R&D analytics and reproducible pipeline execution for genomics teams, as recorded in vendor case documentation. Reported outcomes from the implementation include query runtimes improving by up to 600x and ETL pipelines accelerating by approximately 10x, supporting Regeneron efforts to accelerate drug discovery.
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Oil, Gas and Chemicals | 150 | $200M | Tunisia | Databricks | Databricks Data Intelligence Platform | ML and Data Science Platforms | 2023 | n/a |
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Buyer Intent: Companies Evaluating Databricks Data Intelligence Platform
- University of Southern California, a United States based Education organization with 19957 Employees
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