Application integration · AI pipelines
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.
How the integration works
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
Training corpora, model weights, checkpoints, model registry, and vector snapshots, all protected natively with last-write RPO.
Tamper-evident reconstruction. An attacker can’t corrupt what they can’t reassemble.
PII, PHI, and financial data with no single site holding reconstructable data.
Standard S3. Your training and inference paths are unaffected.
