Minato, 107-0052,
Japan
Afeela Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Afeela and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 160 Afeela employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Afeela has purchased the following applications: Google Cloud Managed Lustre for Cloud Storage in 2025 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Afeela is running and its propensity to invest more and deepen its relationship with Google or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing Afeela revenues, which have grown to $67.0 million in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for Afeela intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Legacy | Google Cloud Managed Lustre | Cloud Storage | IaaS | n/a | 2025 | 2025 |
In 2025, Afeela implemented Google Cloud Managed Lustre as a Cloud Storage component to accelerate AI model training for AFEELA Intelligent Drive. The deployment in Japan targets ADAS and perception model workloads and is positioned to provide higher throughput and faster checkpoint performance for training pipelines.
The implementation leverages Google Cloud Managed Lustre core capabilities, including a parallel POSIX file system architecture, scalable metadata handling, and high throughput data striping to support large batch training and frequent checkpoint operations. Configuration emphasis is on sustained read and write throughput, checkpoint snapshotting, and integration with model training workflows to reduce I/O bottlenecks during distributed training.
Operationally the service is integrated into Google Cloud compute-based training pipelines and used by Afeela engineering and data science teams responsible for AFEELA Intelligent Drive model development. Google Cloud and DDN testimonials are cited for similar ADAS oriented deployments in Japan, and Afeela reports roughly 3x faster model training compared with other Google Cloud storage options, reflecting improved throughput and checkpoint performance for production AI training workloads.
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