List of Amazon Inferentia Customers
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Since 2010, our global team of researchers has been studying Amazon Inferentia 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 Amazon Inferentia 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 Amazon Inferentia for ML and Data Science Platforms include: HCLTech, a India based Professional Services organisation with 223420 employees and revenues of $13.60 billion, Mimecast, a United Kingdom based Professional Services organisation with 649 employees and revenues of $240.0 million and many others.
Contact us if you need a completed and verified list of companies using Amazon Inferentia, 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 Amazon Inferentia 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 | Insight Source |
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HCLTech | Professional Services | 223420 | $13.6B | India | Amazon Web Services (AWS) | Amazon Inferentia | ML and Data Science Platforms | 2023 | n/a | In 2023, HCLTech announced a collaboration with Amazon Web Services that explicitly included deployment of Amazon Inferentia as part of its GenAI infrastructure. The announcement made in New York and Noida on August 23, 2023 links HCLTech to AWS GenAI offerings and identifies Amazon Inferentia by name, Apps Category "". HCLTech positioned Amazon Inferentia to accelerate model inference workloads within an AWS-centric architecture alongside Amazon Bedrock, Amazon Titan and AWS Trainium, while using Amazon CodeWhisperer across its engineering organization. The implementation narrative centers on using Amazon Inferentia for high-throughput, low-latency inference serving for GenAI models, combined with model development workflows that leverage CodeWhisperer for developer productivity and secure code generation. HCLTech also described integration points between its Advantage Cloud platform and AWS developer tooling to automate migration and rehosting, with a centralized dashboard to plan and monitor treatments. Operational scope described in the announcement covers internal use by over 50,000 HCLTech engineers, cloud practitioners and developers, and extension of capabilities to client engagements including industry-specific solutions such as Ziva for financial services. Governance emphasis in the collaboration centers on responsible AI practices and secure application development, with HCLTech committing to instrumenting developer workflows and cloud migration dashboards to manage rollout and oversight across its AWS deployments. | |
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Mimecast | Professional Services | 649 | $240M | United Kingdom | Amazon Web Services (AWS) | Amazon Inferentia | ML and Data Science Platforms | 2024 | n/a | In 2024, Mimecast implemented Amazon Inferentia as a core inference accelerator within its AWS-hosted AI stack. Apps Category: Mimecast deployed Amazon Inferentia alongside Amazon SageMaker to host and run hundreds of deep learning models that profile human communication patterns for email protection. The implementation focused on low-latency inference, enabling per-message analysis in approximately 200 milliseconds while processing roughly two billion emails daily, and it leverages Amazon Inferentia chips to reduce inference cost by about 40 percent as reported by the vendor. Amazon Inferentia is explicitly used to scale high-throughput model serving for production-grade, real-time threat detection. The functional scope centers on human risk management and email security, where models analyze writing style, timing, tone, and thousands of input factors to detect AI-generated and anomalous messages with high confidence. Operational coverage includes global email protection for over 26 million end users, and the deployment runs inside Amazon SageMaker for model hosting, model development workflows, and continuous inference. Integrations are concentrated on the AWS AI stack, with Amazon SageMaker providing orchestration and Amazon Inferentia providing optimized inference acceleration. Governance and product rollout were driven by co-development with AWS, incorporating AWS design best practices for efficient model operation and accelerated time to market. Mimecast used AWS Marketplace for strategic go-to-market support and launched a new social engineering protection service within one year, a timeline the company attributes to the integrated AWS tooling and deployment pattern. The implementation emphasizes operational reliability, model lifecycle management in SageMaker, and infrastructure abstraction so the security engineering teams can focus on model improvement rather than low-level infrastructure. Outcomes explicitly stated by Mimecast include reduced inference costs through Amazon Inferentia and prevention of approximately USD 2.5 million in fraudulent transfers per month by a newly launched product. The architecture prioritizes high-throughput, low-latency inference for production security workloads, with model hosting and inference concentrated on Amazon SageMaker and Amazon Inferentia to balance performance, scale, and cost. |
Buyer Intent: Companies Evaluating Amazon Inferentia
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