---
title: "S3-Compatible Object Storage for AI | Shelby"
description: "S3-compatible object storage for AI, agents, and distributed compute. One address, global access, and a cryptographic record created at write."
canonical: "https://shelby.xyz/"
---

# The Verifiable Data Platform for Distributed Compute

Use the compute that fits each workload without moving and copying your data every time it changes.

- Distributed Training
- Robotics & Physical AI
- Model Cache & Checkpoints
- Agentic Systems

**Talk to us**

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The Problem

## Your data layer shouldn't limit your compute choices.

MEET SHELBY

## Your data, available to the compute you choose.

Features

## How Shelby works

### One address, global access.

Keep your tools and workloads connected to the same data, even as your compute changes.

### Fewer copies to manage.

Make the same data available to more workloads without provisioning and maintaining another full copy for every new environment.

### A cryptographic record from the start.

Each upload creates cryptographic evidence of how the data was stored across Shelby.

### S3-compatible

Use the tools and SDKs your team already knows through the same interface.

### Designed to scale with you.

Capacity is sized to your workload profile and grows with your needs.

### Unmetered movement inside Shelby.

Data movement between Shelby locations does not create a Shelby per-gigabyte charge. External egress to the public internet is quoted alongside your capacity rate.

### Built for your environment.

Shelby Managed is onboarding select workloads now. Have specific infrastructure requirements? Talk to us.

Use cases

## Where Shelby Matters

### Agentic Systems

Give agents persistent access to data across sessions, models, and machines with the same interface and a record created at write.

### Robotics • Physical AI

Keep data accessible across distributed pipelines - collected in one location, processed in another and trained in a third.

### Model Cache • Checkpoints

One origin for weights and checkpoints - reused across supported environments without recreating model state for each one..

### Distributed Training

Run training across changing compute environments without rebuilding the data layer or adding more staging and copying.

teams behind shelby

## **Engineered by **[Jump Trading Group's](https://www.jumptrading.com/)** high-frequency systems and **[Aptos’](https://aptosnetwork.com)** global infra experience.**

### Let’s talk about your data.

One address, global access. Cryptographic record from the start.

**Talk to us**