SELECT
sample_id,
features,
label
FROM dataset
WHERE valid=1
Scanned Rows840M
Valid Samples12.4M
Duration1.2s
Instancequery-eng-1

AI starts with big data

Data engineering is the foundation of every AI initiative. Run data-intensive workloads where your data belongs, on hardware you control.

No egress fees
Self-service provisioning
Data stays on-prem

Predictable economics

One-time purchase. No monthly cloud bills that scale with your data. No egress fees.

Cost comparison graph showing Oxide savings over time

Cloud-native automation

API-first automation for Terraform, Airflow, and orchestration tools. Deploy Apache Spark and data pipeline tooling directly.

Cloud-native automation interface

Verified infrastructure

Verifiable from firmware to API. Run sensitive AI and ML data on an open source stack you can inspect.

Hardware root of trust boot chain diagram
Fig. 1
Root of trust

Public cloud AI vs Oxide

Public Cloud AI vs Oxide comparison
Public Cloud AI
Oxide
Cost
Variable fees, expensive at scale
Fixed infrastructure cost
Data control
Sensitive data leaves your control
Data never leaves your authority
Capacity
Constraints during peak demand
Provisioned capacity always available
Data transfer
Egress fees for large datasets
Zero data transfer fees
Visibility
No visibility into infrastructure security
Verifiable from firmware to API

Your data stack runs unchanged

Standard data pipeline frameworks and tooling. No proprietary platform required.

Official integrations

Plus broad compatibility

Oxide runs standard VMs, so your existing toolchain works out of the box

Prometheus logoPrometheus
Grafana logoGrafana
Apache Spark
Apache Kafka
Apache Airflow
Ray
Dask
XGBoost

AI workloads that run on Oxide

The latest Oxide compute sled features AMD EPYC 9005 series “Turin” processors that support CPU-based AI workloads. Reserve valuable GPUs for the workloads that require them.

Classical machine learning

Decision trees, random forests, XGBoost, and statistical models benefit from high core counts and fast memory access.

  • Fraud detection
  • Time-series forecasting
  • Classification & clustering
  • Predictive modeling

RAG & similarity search

Embedding generation, vector operations, and retrieval pipelines. Large memory capacity enables vector operations at scale.

  • Document retrieval
  • Semantic search
  • Knowledge base queries
  • FAISS indexing

Tuned model inference

Fine-tuned models using LoRA and PEFT run efficiently on modern processors. Expert agents, chat services, and decision-making applications.

  • Expert AI agents
  • Customer service bots
  • Content moderation
  • Recommendation engines

Get rack‑scale efficiency

Made possible through hardware and software co-design.
Oxide
▊▊▊▊
▊▊▊▊
▊▊▊▊
▊▊▊▊
▊▊▊▊
▊▊▊▊
Alternative
⎕⎕⎕⎕
⎕⎕⎕⎕
⎕⎕⎕⎕
▊▊▊▊
▊▊▊▊
▊▊▊▊
⎕⎕⎕⎕
⎕⎕⎕⎕
⎕⎕⎕⎕
▊▊▊▊
▊▊▊▊
▊▊▊▊
2
x
Compute density
12
x
Cooling efficiency

Fixed infrastructure cost

One-time purchase. No monthly bills that scale with data volume or compute hours.

No consumption billing

Budget for capacity, not usage. No surprises when workloads spike.

Save over 40%

Through hardware-software co-design that eliminates licensing, egress, and operational overhead.

Own your AI infrastructure
Talk to our team

Resources