List of Stardog Semantic AI Platform Customers
New York, 10014, NY,
United States
Since 2010, our global team of researchers has been studying Stardog Semantic AI 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 Stardog Semantic AI Platform for Generative AI 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 Stardog Semantic AI Platform for Generative AI Platforms include: Boehringer Ingelheim, a Germany based Life Sciences organisation with 54500 employees and revenues of $28.94 billion, NASA, a United States based Aerospace and Defense organisation with 18000 employees and revenues of $24.00 billion, Macmillan Education, a United Arab Emirates based Education organisation with 51 employees and revenues of $6.0 million and many others.
Contact us if you need a completed and verified list of companies using Stardog Semantic AI 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.
The Stardog Semantic AI Platform customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
Boehringer Ingelheim | Life Sciences | 54500 | $28.9B | Germany | Stardog | Stardog Semantic AI Platform | Generative AI Platforms | 2021 | n/a |
In 2021, Boehringer Ingelheim implemented the Stardog Semantic AI Platform to create a semantic layer over its global R&D data lake, using the application as part of its Generative AI Platforms footprint to accelerate research and knowledge discovery. The deployment positioned the Stardog Semantic AI Platform as the central knowledge access layer for R&D workflows, enabling queryable, integrated metadata and domain concepts across disparate study and gene datasets.
The implementation emphasized wiki-style exploration of studies and genes, providing researchers with conversational and navigable knowledge views rather than forcing repeated ETL and dataset copies. Data virtualization was a core capability, allowing analysts and bioinformaticians to query integrated views without creating redundant storage, and reducing the need for traditional ETL pipelines.
Integration scope explicitly included the R&D data lake and global R&D operations, with the rollout governed from the company headquarters in Germany and adopted by research groups and analytics teams worldwide. Governance centered on a centralized semantic model to standardize concepts and reduce duplication, while workflows shifted toward virtualized access and curated knowledge exploration.
The deployment increased efficiency for analysts and bioinformaticians and produced measurable cost savings via data virtualization, reflecting an operational shift in how Boehringer Ingelheim uses Generative AI Platforms for research discovery and data access.
|
|
|
Macmillan Education | Education | 51 | $6M | United Arab Emirates | Stardog | Stardog Semantic AI Platform | Generative AI Platforms | 2018 | n/a |
In 2018, Macmillan Education implemented the Stardog Semantic AI Platform. The deployment was positioned within the Generative AI Platforms category and focused on powering semantic search and research workflows by unifying heterogeneous data sources into a single knowledge graph to enable intent aware search and fast exploration.
The implementation built core knowledge graph architecture inside the Stardog Semantic AI Platform, with workstreams for entity modeling, ontology alignment, semantic indexing, and query optimization to support intent aware retrieval. The build phase lasted 18 month and produced a production knowledge graph of 100 million triples, with the platform tuned for subsecond query performance.
Operational coverage centered on research and publishing functions, bringing knowledge graph driven search into editorial and researcher workflows and supporting approximately 50,000 users. Governance emphasized ontology lifecycle management and access controls to embed semantic discovery into existing workflows, and the deployment centralized diverse data sources to provide consistent, intent aware search across the organization.
|
|
|
NASA | Aerospace and Defense | 18000 | $24.0B | United States | Stardog | Stardog Semantic AI Platform | Generative AI Platforms | 2020 | n/a |
In 2020, NASA implemented Stardog Semantic AI Platform. The Stardog Semantic AI Platform was deployed in the United States as an Enterprise Knowledge Graph to unify engineering and systems data and to support mission-critical decision making within NASA.
As a solution positioned in the Generative AI Platforms category, the implementation centralized semantic models and a knowledge graph layer to improve cross-discipline traceability and reduce time-to-answer for engineering queries. The deployment emphasized unified data representation across engineering and systems engineering domains, enabling consolidated discovery, semantic search, and knowledge-level linking of requirements, designs, and test data.
Stardog became integrated into NASA operations and workflows supporting Artemis-related programs, providing operational coverage across engineering teams engaged in program development and systems integration. Integration focused on embedding the Enterprise Knowledge Graph into mission workflows to surface traceability and lineage across disparate engineering artifacts.
The rollout delivered explicit operational outcomes reported by NASA, including a reported 10x increase in engineering productivity and reduced risk for Artemis-related programs, alongside faster answers to cross-discipline engineering questions as Stardog was incorporated into ongoing NASA operations.
|
Buyer Intent: Companies Evaluating Stardog Semantic AI Platform
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||