Where no cloud has gone before

Hitachi Ventures joins Edgescale’s latest funding round

Hitachi Ventures is excited to participate in Edgescale AI’s latest funding round, as the company builds the foundational infrastructure required to deploy artificial intelligence into the physical world. Enterprises are racing to operationalize AI across manufacturing, energy, and critical infrastructure, yet struggle with a persistent challenge: getting AI out of the cloud and into real-world environments. Edgescale AI is creating the platform that makes this possible — securely, reliably, and at scale.

Status Quo: Implementing AI in the Real World

Enterprises today face mounting pressure to deploy AI into physical-world environments, driven by labor shortages, rising operating costs, safety requirements, and the need to extract more value from existing assets. Unlike digital-first use cases, physical systems and operational technology introduce real-time constraints, legacy integration challenges, and reliability requirements that make AI deployment fundamentally harder. As a result, the long-promised Industry 4.0 transformation has delivered uneven results, with roughly 70% of companies investing in industrial AI failing to move beyond pilot projects, according to the World Economic Forum.

Cloud infrastructure has proven to be a powerful environment for developing and training AI models; however, the cloud was never designed to operate physical assets or to seamlessly distribute software across heterogeneous, resource-constrained devices. Most industrial AI systems are limited to centralized cloud environments and struggle to interoperate with legacy equipment and intermittently connected devices at the physical edge. This mismatch between where AI is built and where it must ultimately run is a core reason so many deployments stall. To compound this, each factory is a “snowflake,” so pilots don’t scale and security becomes an afterthought.

To overcome these limitations, enterprises have historically relied on custom hardware stacks and manually configured software — requiring long integration cycles tied closely to specific use cases. While these approaches can work in isolation, they come with significant drawbacks:

• Slow deployment timelines, often stretching from months to years
• High operational complexity, requiring specialized teams to manage hardware, software, and models
• Security and data governance risks, particularly in regulated or sensitive environments
• Limited scalability, making it difficult to replicate success across sites or facilities

Edgescale AI — Where no cloud has gone before

Edgescale AI replaces fragmented, custom-built edge stacks with a standardized, production-ready AI platform purpose-built for physical operations.

The company’s Virtual Connected Edge (VCE) appliance — The Cube — delivers a fully private, on-prem AI environment that handles memory, inference, orchestration, and tools locally, without reliance on the cloud. Each unit ships ready for deployment and can be installed in days, not months. Once on site, the system automatically discovers and integrates with existing equipment and data streams, allowing models to be continuously fine-tuned on secure, local data while maintaining low latency and high reliability.

At Edgescale, we’re engineering the infrastructure that brings artificial intelligence into the real world. Our work powers AI in the places that keep society running — manufacturing floors, hospitals, utilities, transportation networks, and more. By bridging the gap between the cloud and the physical edge, we enable real-time intelligence where humans and machines work together.

At Edgescale, we’re engineering the infrastructure that brings artificial intelligence into the real world. Our work powers AI in the places that keep society running — manufacturing floors, hospitals, utilities, transportation networks, and more. By bridging the gap between the cloud and the physical edge, we enable real-time intelligence where humans and machines work together.

Section Headline

At Edgescale, we’re engineering the infrastructure that brings artificial intelligence into the real world. Our work powers AI in the places that keep society running.

By bridging the gap between the cloud and the physical edge, we enable real-time intelligence where humans and machines work together. We enable real-time intelligence where humans and machines work together.