Over 5,000 users run confidential compute workloads here. Phala Cloud carved out this foothold by offering something AWS and Google don't quite match—hardware-level encryption for AI models that locks data down even during processing.
You'll get access to TEE-protected infrastructure. Intel TDX virtual machines? Check. NVIDIA's newest confidential GPUs? Those too. H100, H200, and B200 chips all run with encryption active. Performance drops 5%. That's what keeping your training data and inference requests invisible to the cloud provider costs.
Healthcare AI developers face brutal compliance headaches. Phala Cloud lets you deploy models that process sensitive patient data without exposing it to anyone—period. Blockchain-backed attestation verifies execution, so you're not just trusting marketing claims about security.
Pricing starts at $50.37 monthly for a basic confidential VM. GPU instances cost considerably more. An H100 runs $1,737.40. Need serious horsepower? A B200 hits $4,109.90. Per-minute billing helps soften the blow. Storage adds $0.10 per gigabyte monthly.
CLI and Docker support make deployment straightforward enough. You can run pre-configured models (Llama to DeepSeek) with encryption already baked in. Financial services make sense here. Legal tech applications too. Random side projects? Probably not. This security architecture brings complexity you won't need unless regulatory requirements or competitive paranoia demand it.
But here's the thing—if you're building AI that touches truly sensitive information, hardware guarantees matter more than convenience.