Cloud Storage for the Agentic Age
An S3-compatible bucket your agents connect to over MCP, with a live fork of production they can safely work on, zero-egress reads by default, per-agent access control, and a signed record of everything they touch.
Real data
Zero production risk
A live, governed copy of production your agents can branch in seconds. Work in isolation, promote what's good, or roll back to any point in time. Train, test, and experiment freely; production stays untouched.
Zero egress by default
Tune for speed when you need it
Read-heavy agents stay on a zero-egress mix, so automated reads never run up a bill. Latency-sensitive ones optimize for speed across the providers closest to their workloads, set by their credentials.
Each credential sets its own point on the dial. No surprise read bills, no one-size-fits-all trade-off.
The first governed S3-compatible storage for AI: every agent request authenticated, every action scoped by policy, every decision traceable via MCP.
Every file your AI touched
Signed and on record
One line of code gives you a complete, immutable record of every file your AI touches. Signed, searchable, and ready when the audit question arrives.
Multi-Cloud Architecture
How a single file becomes private, provider-agnostic, and always available.
Mixed for resilience·Pinned to your regions·GDPR-safe everywhere
Your data is encrypted before it ever leaves your device.
Files are split and erasure-coded. Each shard alone is meaningless but fully recoverable.
Shards are stored across your chosen jurisdictions, supporting compliance and resilience.
Files are decrypted only for verified users. Every reconstruction is secure and auditable.
Keep your S3 toolsChange one line
IronShard is S3-compatible: your existing SDKs, scripts, and tools work by swapping a single endpoint.
Already have data? Import it over the S3 API.
import boto3 # The only change — swap the endpoint URL s3 = boto3.client( "s3", endpoint_url="https://s3.amazonaws.com", ) # Everything else stays the same s3.download_file("my-bucket", "datasets/dataset.parquet", "local.parquet")
Start over MCP or by hand
Create an account and your first bucket
Connect your agent
Add IronShard to your agent and let it provision and run storage for your workload.
- 1Add the connector
- 2PromptOnce connected, prompt your agent to work with your storage: read, write, branch, snapshot, and more.
Use S3 credentials
Swap one endpoint in your code. Your SDK, your tools, and your API calls stay the same.
- 1Get your S3 credentials Create S3 credentials for your bucket in the console.
- 2Swap the endpointPoint any S3-compatible SDK at IronShard (AWS SDK, boto3, rclone):
s3 = boto3.client( "s3", endpoint_url="https://s3.ironshard.ai", )
For autonomous agents: IronShard is discoverable over MCP, so an agent can find it, create a bucket with no account or OAuth, and evaluate it on its own. Read the docs here.
Both paths share the same account and buckets: your agent works over MCP while your code uses the S3 API.