Why Confidential Training Matters
Centralized training infrastructure exposes datasets and model IP. Phala enables consortium learning and regulated-industry training with hardware isolation.
Training data contains regulated information
Traditional cloud infrastructure exposes sensitive information to operators and administrators.
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Model checkpoints encode proprietary techniques
Hardware-enforced isolation prevents unauthorized access while maintaining computational efficiency.
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Gradient updates can leak training examples
End-to-end encryption protects data in transit, at rest, and critically during computation.
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Consortium partners need data-custody guarantees
Cryptographic verification ensures code integrity and proves execution in genuine TEE hardware.
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Deploy a fully optimized system and upgrade your current setup.
Secure Data Loading
Load training datasets directly from private sources inside TEEs. Your sensitive data never leaves the secure enclave during the entire training pipeline.
Encrypted Gradient Flow
Training gradients stay encrypted end-to-end. Hardware attestation proves your model updates never leaked.
Verifiable Attestation Reports
Every training run generates cryptographic proof that your data remained confidential throughout the process.
Global TEE Infrastructure
Train on distributed TEE clusters worldwide. Scale your confidential training workloads across secure data centers with hardware-level isolation.
Deploy Multi-GPU Training
Launch distributed pre-training jobs on confidential GPU clusters. Slurm and Kubernetes templates with TEE attestation and sealed checkpoint storage.
# Deploy distributed training on TEE cluster
docker run -d \
--name phala-training \
--gpus all \
--device=/dev/tdx_guest \
-v $(pwd)/data:/data \
-v $(pwd)/checkpoints:/checkpoints \
-e WORLD_SIZE=8 \
-e RANK=0 \
-e MASTER_ADDR=10.0.1.100 \
-e MASTER_PORT=29500 \
-e MODEL_CONFIG=/data/llama-70b.json \
-e TRAINING_DATA=/data/consortium/*.jsonl \
-e CHECKPOINT_DIR=/checkpoints \
phalanetwork/training:latest
# Monitor training progress
docker logs -f phala-training
# Training output from sealed environment
# Epoch 1/10: Loss 2.134 | Throughput 1.2M tok/s
# Epoch 2/10: Loss 1.876 | Throughput 1.2M tok/s
# Checkpoint saved: /checkpoints/epoch-2.bin
# Attestation signed: 0x8a9b7c6d...Verify Training Lineage
Generate cryptographic proofs of your training process. Verify cluster attestation, dataset hashes, and reproducible build IDs for auditors and consortium partners.
# Get cluster attestation and training lineage
curl -X POST https://cloud-api.phala.network/api/v1/training/verify \
-H "Content-Type: application/json" \
-d '{
"job_id": "train-consortium-llama-70b",
"verify_cluster_attestation": true,
"verify_dataset_hashes": true,
"verify_checkpoint_lineage": true
}'
# Attestation proves sealed training
{
"verified": true,
"cluster_size": 8,
"tee_type": "Intel TDX",
"dataset_hashes": [
"0x8a9b7c6d...",
"0x1a2b3c4d..."
],
"checkpoint_lineage": "llama-70b-base -> epoch-10.bin",
"reproducible_build_id": "0xfe7d8c9b...",
"timestamp": "2025-01-15T14:30:00Z"
}Industry-Leading Enterprise Compliance
Meeting the highest compliance requirements for your business
Frequently Asked Questions
Everything you need to know about Confidential Training
PERFORMANCE & COST
SECURITY & PRIVACY
TECHNICAL
Start Confidential Training Today
Train large-scale AI models on sensitive datasets with multi-GPU TEE clusters and hardware-enforced encryption.
Deploy on Phala- Multi-GPU TEE clusters
- Consortium learning support
- Sealed checkpoint storage
- Reproducible attestation
- 24/7 technical support
