Mount Thor Raises $45 Million for Apple Silicon AI Cloud

By Daniel Okafor

Mount Thor raised $45 million in equity financing across its Seed and Series A rounds to expand data-center infrastructure for autonomous AI agents.

CRV and Conviction co-led the Series A. Chad Byers and Offline Ventures co-led the Seed.

Founder and CEO Peter Voell said:

“Making Apple’s operating system and silicon available at datacenter-scale is a massive untapped opportunity in AI infrastructure. Decades of investment in accessibility and human-computer interaction make macOS the best place for agents to work and for humans to hold them accountable.”

He added:

“And with chips like the M5 Ultra, Apple silicon is becoming a high performance, more power- and cost-efficient platform for production inference.”

Additional investors included CSC Leasing, Enea Capital, Long Journey Ventures and Upper90. Strategic angel investors were associated with Cognition, Core Automation, Daytona, Meta, OpenAI, Together AI and Vercel.

Mount Thor also secured non-dilutive financing to support hardware purchases, but did not disclose the amount.

CRV General Partner Brittany Walker said:

“Mount Thor sits at the intersection of two important shifts: the rapidly expanding capabilities of autonomous agents and the increasing demand for compute that can support both local and cloud workloads. We’re thrilled to back Peter and the team as they make it easier to use Apple’s platforms at scale for agentic AI.”

The capital will support making macOS and Apple silicon available at cloud scale for AI research, software development, agent deployment and enterprise inference. The San Francisco company was founded in 2026. It builds managed cloud infrastructure that provides access to large fleets of Apple computers and processors.

How does Mount Thor turn Apple hardware into cloud infrastructure?

Mount Thor provisions elastic computing instances powered by macOS and Apple silicon. Customers can provision and release resources as requirements change. The company develops, deploys and manages rack-scale systems of Apple hardware inside data centers.

For AI developers, the platform offers an alternative to buying and managing large numbers of physical Apple devices. Mount Thor said the service is designed to provide the security, scalability, availability and cost efficiency of established cloud providers.

Customers can use managed Apple resources without building dedicated facilities or maintaining large physical fleets. Mount Thor says its infrastructure can support agent workloads that run briefly or continuously.

Mount Thor deployed its first data center in less than six months. It now operates what it describes as one of the largest elastic fleets of Apple silicon hardware.

Why does Mount Thor expect demand for cloud-based macOS to rise?

Mount Thor believes cloud-based macOS demand will increase as AI agents handle more complex tasks for consumers and businesses. Its target market includes computer-use agents that interact directly with software interfaces.

These agents can navigate applications, perform multistep workflows and operate in environments normally used by human employees. Some complete short tasks and terminate. Others run continuously for days or weeks.

That variation creates demand for computing capacity that arrives on demand and preserves software compatibility. Mount Thor also considers macOS important because many business and consumer applications run inside Apple’s ecosystem.

Certain software development, testing and automation tasks require access to Apple’s operating system, the company said. Mount Thor aims to make it easier for developers to run agents against Apple applications and services.

Mount Thor identified four uses for the infrastructure:

• AI research laboratories can create reinforcement learning environments where models train and evaluate behavior through software interfaces.
• Agent infrastructure companies can provision secure macOS sandboxes to test autonomous capabilities without running every experiment on local hardware.
• Long-running agents can operate across multiple devices while retaining a consistent Apple identity.
• Software developers can build, test and simulate applications intended for Apple devices. Mount Thor sees particular value for AI-native platforms that run many tests or simulations at once.

Where does Apple silicon fit in production AI inference?

AI inference means running trained models to generate predictions, responses and other outputs. Mount Thor said inference has become a significant part of infrastructure demand as organizations deploy more AI applications.

The company believes Apple processors offer advantages for selected workloads involving power consumption, performance and operating costs. Mount Thor is targeting enterprises and open-source models optimized for Apple silicon.

It plans an inference laboratory to improve how open-source models run on Apple hardware. Mount Thor believes the lab can help customers assess the economics of production workloads on alternative processor architectures.

Mount Thor says its infrastructure is intended to give enterprises another computing option alongside conventional cloud environments. The company frames the work as part of a broader effort to diversify compute for agentic AI.

How will Mount Thor use the capital and who is building the team?

Proceeds from the equity round will expand Mount Thor’s data-center footprint and available computing capacity. The company also plans to recruit employees across infrastructure development, engineering and research.

Mount Thor said its team brings infrastructure experience from major AI and cloud companies. Members previously worked at Cerebras, CoreWeave, Fluidstack, Nebius, OpenAI and xAI. The company said that background provides a foundation for developing large-scale systems for demanding AI workloads.

Mount Thor believes specialized infrastructure can meet requirements conventional cloud offerings do not fully serve. It sees opportunities across research, enterprise software, autonomous agents and application development.

Mount Thor characterized the financing as evidence of investor interest in infrastructure designed specifically for autonomous AI systems. Its longer-term goal is to make Apple silicon accessible for a wider range of AI workloads.

Mount Thor’s next test is execution. The company must add data-center capacity, hire staff and attract sustained agent and inference workloads. Success would determine whether its specialized Apple infrastructure can scale beyond the first facility it deployed in less than six months.