The right hardware for every job.
AtomereAI’s fleet is deliberately mixed. Each workload family gets the accelerators, interconnect, and storage profile it actually needs — and they all share one control plane, one network, and one bill.
Foundation-model training
Large, tightly coupled clusters with non-blocking fabric for pre-training and long-running fine-tunes.
- Dense GPU nodes on a lossless fabric
- High-throughput parallel storage
- Checkpoint-aware scheduling
Inference at scale
Latency-sensitive serving that scales with demand, on accelerators sized to the model rather than the largest SKU.
- Right-sized accelerators per model
- Autoscaling endpoints
- Placement close to users
Physical AI
The full robotics loop — world models, simulation, synthetic data, policy training, and evaluation — on one platform.
- Mixed graphics + compute GPUs
- Simulation fleets that scale out
- Large sensor-data pipelines
Simulation & digital twins
Physics, rendering, and digital-twin workloads that need RT cores and high-fidelity graphics as much as raw FLOPs.
- RTX-class rendering GPUs
- Interactive and batch modes
- Streaming to remote clients
Scientific & HPC
Classic HPC and AI-for-science jobs — molecular dynamics, climate, CFD — alongside the models that accelerate them.
- FP64-capable accelerators
- MPI over low-latency interconnect
- Batch schedulers you already know
Data & multimodal pipelines
Curation, labeling, embedding, and video/sensor processing that feed every other workload on the platform.
- CPU-heavy and GPU-light nodes
- Object storage without egress surprises
- Elastic burst capacity
Consume it the way your team works.
Dedicated clusters
Reserved bare-metal capacity with a dedicated fabric for long-running training and research programs.
Managed Kubernetes & Slurm
Bring your existing schedulers and pipelines. We operate the control plane and the hardware underneath.
On-demand & burst
Elastic capacity for inference peaks, simulation sweeps, and data-processing jobs that come and go.
Bring us your hardest mix of workloads.
Tell us what you’re building — we’ll map it to the right hardware, network, and storage, and show you how it runs.
Start a conversation