List of Seldon Core Customers
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Since 2010, our global team of researchers has been studying Seldon Core 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 Seldon Core for AI Frameworks and Libraries 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 Seldon Core for AI Frameworks and Libraries include: AstraZeneca, a United Kingdom based Life Sciences organisation with 94300 employees and revenues of $73.98 billion, Capital One, a United States based Banking and Financial Services organisation with 76300 employees and revenues of $39.11 billion, PayPal, a United States based Banking and Financial Services organisation with 24400 employees and revenues of $31.80 billion and many others.
Contact us if you need a completed and verified list of companies using Seldon Core, 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 | Insight Source |
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AstraZeneca | Life Sciences | 94300 | $74.0B | United Kingdom | Seldon | Seldon Core | AI Frameworks and Libraries | 2020 | n/a | In 2020, AstraZeneca deployed Seldon Core as part of its Predictive Insight Platform PIP to operationalize model serving for its Augmented Drug Design initiative. Seldon Core is applied as an AI Frameworks and Libraries component to provide production-grade model serving and autoscaling, and vendor and industry reporting documents explicit module usage for this implementation. The implementation emphasizes Seldon Core model serving and autoscaling capabilities, configured to expose chemistry, ADME and DMPK models as networked inference endpoints. Deployment pipelines were integrated with GitOps driven CI/CD to push containerized model artifacts and to enforce automated scaling policies, and monitoring and observability were integrated to capture inference metrics and service health. AstraZeneca uses Seldon Core within the Predictive Insight Platform to deploy and autoscale hundreds of drug discovery models, supporting R&D functions across the United Kingdom and focusing on chemistry, ADME and DMPK workflows. Operational coverage spans model lifecycle stages from deployment to continuous monitoring, enabling tighter coordination between data science teams and laboratory decisioning processes. Governance was strengthened through standardized model packaging and GitOps controlled rollout procedures, improving traceability and release controls for models. The implementation shortened model deployment time to under a day and is described as improving governance for AstraZeneca’s Augmented Drug Design effort. | |
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Capital One | Banking and Financial Services | 76300 | $39.1B | United States | Seldon | Seldon Core | AI Frameworks and Libraries | 2019 | n/a | In 2019, Capital One deployed Seldon Core to establish a Model as a Service platform within the AI Frameworks and Libraries category. The deployment targeted production ML serving to enable real time decisioning in financial services across the United States. The implementation leveraged Seldon Core and Seldon Core Plus capabilities to provide model serving, online inference, canary and A/B deployments, and production monitoring as core components of the bank's MLOps platform. Seldon Core served as the application layer for model lifecycle operations, handling packaging, routing, model version management, and automated traffic shifting for staged rollouts. Operational scope centralized ML model deployment workflows for data science and engineering teams, shortening handoffs between development and production and supporting real time decisioning pipelines across United States operations. Integration focus was on embedding served models into live decision workflows and instrumenting production monitoring for model performance and availability. Governance and rollout were structured around staged deployment patterns, canary and A/B controls, and production monitoring to enforce promotion and rollback policies for models. The implementation dramatically reduced ML model deployment time from months to minutes, accelerating productionization of models for Capital One's financial services use cases. | |
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PayPal | Banking and Financial Services | 24400 | $31.8B | United States | Seldon | Seldon Core | AI Frameworks and Libraries | 2021 | n/a | In 2021, PayPal implemented Seldon Core to operationalize and govern ML model deployments at scale for payment and fraud-related applications in the United States. The deployment uses Seldon Core as the AI Frameworks and Libraries layer to support production inference, governance, and lifecycle management across payment and fraud detection workloads. Architecturally the implementation centers on containerized model serving, inference orchestration, and runtime model management, with inferred usage of model serving, monitoring, and explainability capabilities consistent with Seldon Core's enterprise MLOps positioning. Teams configured Seldon Core to host multiple model endpoints, enable telemetry for model performance and data drift, and surface explainability outputs alongside inference results for downstream risk and review workflows. Operational scope is concentrated in the United States and spans PayPal engineering and risk operations responsible for payments and fraud functions, establishing model change controls and operational governance for production models. The implementation introduced model lifecycle workflows, including versioning, rollout controls, and monitoring-driven alerting, positioning Seldon Core as the runtime governance plane for ML within PayPal's fraud and payment operations. |
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