Application integration · AI pipelines

Protect the data your models are made of.

Training corpora, model weights, checkpoints, and vector embeddings are the assets attackers want and the ones you can’t rebuild. ML frameworks and vector databases write to S3; through Myota, every AI asset is encrypted and Shard and Spread™ at write time.

Talk to us AI & data lake use case

How the integration works

A protected S3 endpoint for the whole pipeline

PyTorch, TensorFlow, Hugging Face, MLflow, and vector databases like LanceDB write over standard S3 to Myota. Datasets, weights (.pt, .safetensors), checkpoints, and embeddings land as encrypted shards spread across independent locations. Restore is a remount, not a rebuild, and a compromised location yields only unreconstructable fragments.

What it delivers

Native-format protection for AI assets

The whole pipeline, in place

Training corpora, model weights, checkpoints, model registry, and vector snapshots, all protected natively.

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Poison-resistant

Tamper-evident reconstruction. An attacker can’t corrupt what they can’t reassemble.

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Regulated training data

PII, PHI, and financial data with no single site holding reconstructable data.

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No pipeline changes

Standard S3. Your training and inference paths are unaffected.

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