near-ai-cloud
NEAR AI Cloud private inference and verification. Use when integrating NEAR AI Cloud API for verifiable private AI inference, verifying model or gateway TEE attestation (NVIDIA NRAS, Intel TDX), verifying chat message signatures, implementing end-to-end encrypted chat, using specialized TEE endpoints (embeddings, reranking, images, audio, PII redaction), or using the OpenAI-compatible API with NEAR AI Cloud.
How do I install this agent skill?
npx skills add https://github.com/near/agent-skills --skill near-ai-cloudIs this agent skill safe to install?
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This skill provides documentation and integration guides for the NEAR AI Cloud, focusing on verifiable private AI inference using Trusted Execution Environments (TEEs). It includes instructions for hardware attestation (NVIDIA, Intel), end-to-end encryption (E2EE), and chat signature verification. No malicious patterns were detected.
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What does this agent skill do?
NEAR AI Cloud
Verifiable private AI inference through Trusted Execution Environments (TEEs). All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs — your data stays encrypted and isolated from infrastructure providers, model providers, and NEAR itself.
Quick Start
The API is OpenAI-compatible. Point any OpenAI SDK at https://cloud-api.near.ai/v1:
import openai
client = openai.OpenAI(
base_url="https://cloud-api.near.ai/v1",
api_key="YOUR_API_KEY" # from cloud.near.ai dashboard
)
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V3.1",
messages=[{"role": "user", "content": "Hello, NEAR AI!"}]
)
print(response.choices[0].message.content)
import OpenAI from 'openai';
const openai = new OpenAI({
baseURL: 'https://cloud-api.near.ai/v1',
apiKey: 'YOUR_API_KEY',
});
const completion = await openai.chat.completions.create({
model: 'deepseek-ai/DeepSeek-V3.1',
messages: [{ role: 'user', content: 'Hello, NEAR AI!' }]
});
console.log(completion.choices[0].message.content);
How It Works
- All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs
- TLS terminates inside the TEE, not at a load balancer — prompts are never exposed in plaintext
- TEEs generate cryptographic attestation proofs verifiable via NVIDIA NRAS and Intel TDX
- Every chat response is signed by a key that never leaves the TEE
- You can independently verify hardware attestation and bind it to message signatures
Verification Flow
1. Generate nonce
2. Request model attestation → get signing_address, nvidia_payload, intel_quote
3. Verify GPU attestation → submit nvidia_payload to NVIDIA NRAS, check JWT fields
4. Verify CPU attestation → verify intel_quote via dcap-qvl or TEE Explorer
5. Verify GPU-CPU binding → signing_address + nonce bound in TDX report data; same nonce in NRAS eat_nonce
6. Make chat request → use the API as normal
7. Fetch chat signature → GET /v1/signature/{chat_id}
8. Verify signature → recover signer, compare to attested signing_address
API Endpoints
Base URL: https://cloud-api.near.ai
| Endpoint | Method | Description |
|---|---|---|
/v1/chat/completions | POST | OpenAI-compatible chat completions |
/v1/models | GET | List available models |
/v1/attestation/report?model={model} | GET | Model attestation (GPU + CPU) — requires API key |
/v1/attestation/report | GET | Gateway attestation — requires API key |
/v1/signature/{chat_id} | GET | Chat message signature (also covers Responses API resp_*) |
Critical Knowledge
- Base URL is
https://cloud-api.near.ai/v1— use with any OpenAI SDK signing_algocan beecdsaored25519- Attestation report now requires an API key —
Authorization: Bearer <key>; retrieval is free and non-billable - Nonce should be a random 64-char hex string (32 bytes) for attestation freshness
- NRAS response is a two-part array:
[["JWT", "..."], {"GPU-0": "..."}]— overall JWT + per-GPU JWTs - The
signing_addressfrom model attestation must match the address that signed chat messages - Chat signatures are persistent and can be queried at any time after completion
References
| Topic | File |
|---|---|
| Private vs Anonymised Models | references/private-vs-anonymised.md |
| Model TEE verification | references/model-verification.md |
| Gateway verification + TLS | references/gateway-verification.md |
| Chat message verification | references/chat-verification.md |
| E2E encrypted chat (E2EE) | references/e2ee-chat.md |
| Specialized endpoints | references/specialized-endpoints.md |
Upstream Docs (prefer live values)
- OpenAI compatibility — streaming, reasoning, Files API behavior
- Stateless Responses API —
resp_*stateless responses - Prompt caching
- Web search — server-side live web results
- Staking for inference — pay with staking rewards
- Usage reporting API
- Model discovery & refresh
Resources
- NEAR AI Cloud: https://cloud.near.ai
- Documentation: https://docs.near.ai/cloud/introduction- Verification Example: https://github.com/near-examples/nearai-cloud-verification-example
- Full Verifier: https://github.com/nearai/nearai-cloud-verifier
- NVIDIA NRAS API: https://docs.api.nvidia.com/attestation/reference/attestmultigpu_1
- TEE Attestation Explorer: https://proof.t16z.com/
- DCAP QVL (TDX verification): https://github.com/Phala-Network/dcap-qvl
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
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