TAHO, a new infrastructure startup founded by former engineers from Meta, Google, and Snap has raised $3.5 million to accelerate the development of a distributed compute platform designed specifically for modern AI workloads.
The company is building a next-generation compute fabric that promises massive speed improvements and dramatically lower costs for organizations struggling to keep up with the escalating demand for AI training and inference.
A Compute Platform Designed for Soaring AI Demand
“AI workloads are increasing faster than the world can expand traditional infrastructure,” said Todd Smith, TAHO’s co-founder and CEO.
He said the team set out to build a universal compute layer that is fast enough and cost-efficient enough to keep AI-driven companies growing sustainably.
TAHO’s vision is to remove the bottlenecks that slow down machine learning teams today — fragmented infrastructure, siloed resources, and orchestration frameworks that were never built with GPU-intensive workloads in mind.
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A Distributed Fabric That Behaves Like One Giant Machine
Instead of relying on container orchestrators like Kubernetes, TAHO introduces a federated execution model that unifies machines, clusters, and nodes into a single compute fabric.
Key capabilities include:
- Breaking workloads into discrete micro-tasks that can run anywhere capacity is available
- Coordinating distributed execution in real time
- Reassembling results globally while avoiding redundant processing
- Running training, inference, and data movement with high efficiency
According to the company, this architecture allows compute jobs to finish up to 10x faster while cutting costs by up to 90%, especially for organizations running continuous or large-scale AI operations.
“Modern AI workloads push past what legacy orchestration tools were built to handle,” said Michal Ashby, CTO and co-founder. “Our architecture treats an entire fleet of compute as a single intelligent system and optimizes everything around that idea.”
Positioning for 2026 Launch
TAHO’s seed round was backed by a group of strategic angels and industry veterans familiar with the challenges of scaling AI infrastructure.
The new capital will support engineering expansion, deeper platform development, and onboarding of early pilot customers ahead of a broader commercial rollout targeted for 2026.
“Our aim is straightforward,” Smith said. “Help companies squeeze more performance out of the hardware they already pay for — and make advanced AI workloads faster, cheaper, and far easier to operate.”
About TAHO
TAHO builds a distributed compute fabric that turns cloud and data-center resources into a unified high-performance system. Designed by alumni from Meta, Google, and Snap, the platform accelerates AI workloads, reduces compute costs, and provides an alternative to traditional orchestrators. TAHO’s mission is to bring supercomputing-grade performance within reach for every organization.
