IDrive e2 Opens Tokyo Storage Region for AI and Data Workloads

Apr 28, 2026
IDrive e2 has launched a new storage region in Tokyo, marking its first in Japan and expanding its global network to enhance performance and accessibility for AI and data-intensive applications.

IDrive e2 has opened a new storage region in Tokyo, Japan, its first in the country, announced in a press release. The expansion aims to deliver faster, S3 compatible object storage for customers in East Asia.

The Tokyo region provides lower latency, faster data access, and improved reliability by bringing storage closer to users. It supports workloads such as AI and large-scale data processing that benefit from high throughput and reduced network delays.

With this addition, IDrive e2 now operates more than 14 storage locations across the United States, Canada, Europe, and Asia. The company offers pricing starting at $49.50 per terabyte per year or $5 per terabyte per month on a pay-as-you-go basis, with no extra fees for egress or API calls. Customers in Japan can now store and access data locally for improved performance and compliance.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

AI Chips & Datacenters AI Brief AI Brief (X)
Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Guide
Private AI chip companies, by latest reported valuation

Private AI chip companies, by latest reported valuation

Private companies building AI compute silicon (the chips that run AI workloads), shown with each company's most recent reported or disclosed valuation. The figures are measured on different dates and bases, so this is a snapshot, not a live ranking or a like-for-like comparison.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.