We transform complex compute
into AI systems that perform

DataInfrastructureInferencePost-training

Capacity exists — but sits idle.

Modern AI depends on large-scale data,
GPU clusters, and distributed compute.
Most infrastructure wasn't built for this.

Modern AI depends on large-scale data, GPU clusters, and distributed compute. Most infrastructure wasn't built for this.

Project Meridian builds the infrastructure
that makes unused compute usable, at scale.

Project Meridian builds the infrastructure that makes unused compute usable, at scale.

Infrastructure visualization

Four integrated layers.
One coherent system.

01

Infrastructure Orchestration

Systems for organizing GPUs, clusters, and distributed compute environments required to train and operate large-scale AI models.

02

Inference Systems

Systems for organizing GPUs, clusters, and distributed compute environments required to train and operate large-scale AI models.

03

Post-Training Pipelines

Systems for organizing GPUs, clusters, and distributed compute environments required to train and operate large-scale AI models.

04

Enterprise Data Systems

Systems for organizing GPUs, clusters, and distributed compute environments required to train and operate large-scale AI models.

Enterprise Intelligence

RAGs • AI Agents • AI Workflows

MERIDIAN LAYER

Agentic AI Cloud

RL Envs • Sandboxes • Data Pipelines

AI GPU Cloud

Training F/W

PT • SFT • RL

Inference F/W

Spec • Bench

Gpu Cloud

Orchestration • Storage • Compute

Data Centers + Infra

Four integrated layers.
One coherent system.

Working directly with teams
building modern AI infrastructure

Emerging Cloud Providers + Data Centers

Operate AI-native cloud infrastructure

GPU clusters and storage infrastructure become coordinated environments capable of supporting modern AI workloads.

Audience Card 1

Distributed
model training

High-Throughput
Inference Environments

GPU Cluster
Orchestration

AI-Ready Compute
Infrastructure

Audience Card 2

Production
Inference Systems

Fine-Tuning & Internal
Model Training

Enterprise AI
Platforms

Distributed Compute
Coordination

Enterprise AI Platforms

Build internal AI platforms

Existing compute infrastructure can be organized into cohesive environments capable of supporting internal AI development and deployment.

Every deployment is different.

Want to know what your infrastructure will cost and return? Share your setup with us and we'll model the exact costs, utilization, and ROI for your scenario.

Power & Cooling

Full cost breakdown for your GPU cluster and cooling setup

Power draw • PUE • Operating costs

Inference ROI

Revenue potential and payback period modelled to your traffic

Cost/inference • Payback period

Built with Meridian

Infrastructure

Operate AI-native cloud

Transform existing data centers into coordinated AI infrastructure with distributed compute orchestration.

Expected Outcome

Transform existing data centers into coordinated AI infrastructure with distributed compute orchestration.

AI Development

Build faster AI pipelines

Accelerate model development with integrated training, fine-tuning, and deployment workflows.

Expected Outcome

Transform existing data centers into coordinated AI infrastructure with distributed compute orchestration.

Enterprise

Deploy internal AI systems

Build enterprise AI applications with secure data pipelines and compliance-ready infrastructure.

Expected Outcome

Transform existing data centers into coordinated AI infrastructure with distributed compute orchestration.

Ongoing confidential deployments across emerging neo-cloud providers and enterprise AI platforms

Ready to build the next generation of AI infrastructure together?