List of TerminusDB Customers
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Since 2010, our global team of researchers has been studying TerminusDB 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 TerminusDB for AI Database 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 TerminusDB for AI Database include: University of Oxford, a United Kingdom based Education organisation with 16905 employees and revenues of $4.17 billion, Thirdfort, a United Kingdom based Professional Services organisation with 106 employees and revenues of $12.0 million, Clarus Care, a United States based Healthcare organisation with 30 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using TerminusDB, 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 TerminusDB 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!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Clarus Care | Healthcare | 30 | $10M | United States | Data Chemist | TerminusDB | AI Database | 2020 | n/a |
In 2020 Clarus Care deployed TerminusDB, an AI Database from Data Chemist, as a core data layer supporting its healthcare call management platform in the United States. The deployment paired TerminusDB with a serverless application architecture to support clinical call routing and operational decisioning at runtime.
TerminusDB was implemented to provide graph based data modeling, version control and query services typical of an AI Database, enabling structured representation of call workflows and event histories. The application architecture ran on AWS services with API Gateway, SQS and Lambda functions handling inbound calls and asynchronous processing, while Dashbird provided serverless observability for Lambda, API Gateway and SQS to surface real time operational telemetry and alerts.
Operational coverage focused on healthcare operations and incident response in the United States, with Dashbird alerts feeding into Clarus Care's monitoring and on call processes to reduce potential patient impact. Dashbird’s alerts helped Clarus avoid any patient call impact during the November 2020 AWS outage and supported improvements in API response times and reduced infrastructure costs according to the vendor case study.
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Thirdfort | Professional Services | 106 | $12M | United Kingdom | Data Chemist | TerminusDB | AI Database | 2025 | n/a |
In 2025, Thirdfort deployed TerminusDB as its AI Database to support knowledge management and programmatic data access for core data engineering and product analytics functions. Thirdfort TerminusDB AI Database implementation was positioned to centralize graph-oriented datasets and enable reproducible dataset versioning across development and operational teams.
The TerminusDB rollout emphasized category-aligned capabilities, including graph-based knowledge modeling, schema version control, repository-level transaction tracking, and API-driven query access to support both graph and document style workflows. Configuration work focused on schema design, ingestion pipelines, change provenance, and collaborative editing controls to maintain traceability of data and models.
Deployment architecture was provisioned for API-first integration with existing data pipelines and developer toolchains, with role-based access controls and audit logging applied to production and staging repositories. Operational coverage included engineering, product analytics, and data operations teams, with repository lifecycle practices to separate experimental datasets from governed production knowledge graphs.
Governance and rollout followed staged repository provisioning, schema governance reviews, and developer onboarding to enforce modeling standards and query patterns. Data Chemist supported the deployment and operationalization of TerminusDB, concentrating on repository lifecycle management, automation of validation workflows, and operationalizing CI oriented processes for dataset validation and release control.
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University of Oxford | Education | 16905 | $4.2B | United Kingdom | Data Chemist | TerminusDB | AI Database | 2015 | n/a |
In 2015, the University of Oxford implemented TerminusDB as part of the ALIGNED project and associated Seshat research work, establishing an AI Database-backed research and academic data infrastructure. Oxford used TerminusDB for linked-data modelling, formal validation and large interdisciplinary data curation across project teams in the United Kingdom.
Implementation leveraged TerminusDB’s schema and WOQL capabilities together with built-in versioning, applying formal schema design, commit-style version control and validation rules to manage evolving ontologies and datasets. These functional elements were configured to enable collaborative curation, provenance capture and data-quality tooling for Oxford-linked research projects.
Deployment was oriented around project-level repositories used by ALIGNED and Seshat collaborators, covering multiple research groups and interdisciplinary datasets rather than a centralized administrative rollout. Operational scope focused on research data management, curation workflows and cross-team collaboration between academics and data stewards.
Governance centered on schema governance and version-control-driven workflows, embedding validation in ingestion and curation processes and providing audit trails for iterative edits. University of Oxford TerminusDB AI Database supported structured data governance practices within project workflows and enabled reproducible linked-data modelling and quality assurance across participating research teams.
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