AI Agent Storage with Built-In Audit Trails
Most object storage was built before AI agents existed. IronShard is S3-compatible object storage built for the AI era, so everything your agents read, write, or query is authenticated, logged, and provable.
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.
Real data.
Zero production risk.
A live, policy-enforced copy of production your AI can safely train on, test against, and experiment with. Fork a branch, run your workload, discard or promote. Production stays clean.
The first governed S3-compatible storage for AI: every agent request authenticated, every action scoped by policy, every decision traceable via MCP.
Every agent request passes through six checkpoints. Here is what happens inside one.
Geo-Distributed Storage
for Automation and Compliance
Connect What You
Already Have.
IronShard provides fully managed storage out of the box or connects to the S3-compatible buckets you already use. No migration, no vendor lock-in, no custody transfer. Your data stays in your accounts. IronShard adds governance, not ownership.
Learn moreMulti-Cloud Architecture
IronShard protects data with end-to-end encryption, erasure-coded fragmentation, and multi-cloud distribution. Your data is private, provider-agnostic, and always available.
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, ensuring compliance and resilience.
Files are decrypted only for verified users. Every reconstruction is secure and auditable.
Predictive Caching for AI Workloads
Seamless S3 Compatibility
IronShard is built with 100% S3 API compatibility, making integration with your existing infrastructure effortless. The tools, scripts, and workflows you rely on work without modification.
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")
Auditable from
Day One.
From the day you connect, every action your AI agent takes is logged, governed, and exportable. When the audit question arrives — from a regulator, a client, or your own team — the answer already exists.