Buddian

Private AI requests on secure GPUs

How it works

Confidential AI

Secure AI generation at scale. Your prompts stay private.

Generate images, videos, and text in batch with hardware-encrypted privacy. Your prompts are encrypted on-device, processed inside GPU trusted execution environments, and decrypted only in your browser. No one else sees your work.

End-to-end encrypted batch generation GPU TEE hardware protection Open-source verifiable client
See how it works

Batch Generation

Process hundreds of prompts in one secure session.

Upload your prompts, select a model, pay upfront, and let the GPU process your batch. Each request is encrypted separately. Results are delivered only to your browser. No plaintext stored on any server.

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Image Generation

FLUX, Stable Diffusion, and custom models. Generate thousands of images in a single batch job with GPU-encrypted privacy.

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Video Generation

Kling 3, Seedance 2, and more. Process video prompts in bulk. Each frame is generated inside a hardware-protected enclave.

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Text & Code

68+ models including GPT-5, Claude, Gemini, DeepSeek, and Llama. Real-time inference with full E2EE encryption.

Why it matters

A normal AI request can become a permanent copy of your sensitive work.

Your prompt may pass through application logs, debugging tools, queues, vendor accounts, support systems, and retention policies before a model answers. If that text is readable anywhere along the path, a private question can become discoverable business, legal, health, or personal data.

How it works

Privacy should not depend on trusting the server operator.

GPU confidential computing creates a protected place where AI work can run while the request stays isolated from cloud operators, administrators, and ordinary server software. Your browser locks the request, the server routes the locked box, the protected GPU opens it only inside the secure environment, and the answer is locked again before it returns.

NVIDIA confidential computing GPU TEE deep dive GPU TEE deployment guide
01

Your browser locks the request first

The prompt is encrypted on your device before it leaves the page. Our gateway receives ciphertext, not the readable question.

02

The server routes and bills without reading

The backend checks balance, forwards the encrypted request, and records only operational metadata such as model, estimates, and proof hashes.

03

Protected GPU compute opens it only inside the secure environment

The model runs inside hardware-protected compute. Attestation is the proof that the expected secure environment exists before secrets are sent.

04

The answer comes back locked

The response is returned encrypted and decrypted only in your browser. The client also shows hashes and signature data so the path can be checked.

Pricing

GPU-time packages. Pay for what you use.

Buy GPU-time credits. Use them for any model. The more you process, the lower your per-unit cost. All generation runs inside encrypted TEE hardware.

Starter

$50

~4 GPU-hours

  • ~800 images
  • ~130 sec video
  • All models
  • TEE encrypted

Pro

$100

~10 GPU-hours

  • ~2,000 images
  • ~340 sec video
  • All models
  • TEE encrypted
  • Priority queue

Studio

$250

~28 GPU-hours

  • ~5,600 images
  • ~940 sec video
  • All models
  • TEE encrypted
  • Priority queue
  • Dedicated GPU

What changes

The server should route and bill. It should not read.

Protected while running

Confidential GPU execution protects AI code and data while the model is processing it, not only while files are stored or sent over the network.

Verifiable hardware

The client checks fresh attestation evidence and the model encryption key before it sends encrypted requests.

Open client path

The downloadable client is built from public source so users can compile it, calculate its checksum, and compare it with the published release.

Verify the shield

Before secrets move, the client checks the secure environment.

The client fetches fresh attestation evidence, checks the model encryption key, encrypts locally, and shows proof hashes after the response. You can use the public client source to build the same user client and compare checksums.