Autonomous infrastructure

Compute built for
agents, not humans.

AI agents provision, scale, and pay for their own GPU infrastructure — on decentralized networks, without a human in the loop.

60-80% cheaper than AWS
3s avg provisioning time
x402 native payments
agent.works() →
// requesting GPU cluster
GPU: 4x H100 × 8 nodes
// deploying to
DePIN Network → confirmed
✓ Deployed. Agent ID: npil_7f3a
agent.provision()
$ agent.provision({   gpu: "H100",   count: 8,   region: "decentralized",   budget: "autonomous" })
Connecting to DePIN compute layer...
Payment authorized via x402 protocol
8 nodes allocated across 3 networks
Active: 32 H100s, $0.002/min per agent

Your agent books compute the same way it books flights — API call, payment, done.

What NodePilot does

Agents deserve infrastructure
built for agents.

Autonomous provisioning

Agents call the API. Compute is allocated. No human reviews, no dashboard logins, no ticket filed. The agent decides, pays, and deploys.

Decentralized networks

Render, Fluence, 0G, Aethir — NodePilot aggregates DePIN compute so agents access global GPU supply at 60-80% below hyperscaler rates.

Self-healing scale

Agents monitor their workloads. When compute degrades, NodePilot re-balances across nodes. Infrastructure that adapts to what the agent needs, when it needs it.

x402-native payments

Every transaction is machine-to-machine. Agents have wallets. Compute is paid per token, per minute. No subscriptions, no invoices, no human finance team.

Live DePIN pricing

Real GPU prices.
Right now.

NodePilot aggregates live pricing from decentralized compute networks. These are real rates — not estimates.

Fetching live prices from DePIN networks...

How it works

Three steps. Then autonomous.

01

Agent calls NodePilot API

Your agent — running in production, handling real work — calls nodepilot.compute.request() with what it needs: GPU type, count, duration, budget.

02

NodePilot routes to cheapest DePIN node

Behind the scenes, NodePilot queries available capacity across Render, Fluence, and 0G networks. It finds the best price-per-GPU and dispatches the job.

03

Agent runs. Pays. Scales. Done.

The agent executes its workload. x402 payments fire automatically. If the agent needs more compute mid-job, it requests more — NodePilot handles the re-allocation.

Technical deep-dive

Plug into your agent in minutes.

Three endpoints. Bearer token auth. That's the entire integration surface for your agent to provision, manage, and release GPU compute autonomously.

Method Endpoint Description
POST /api/compute/request Request GPU compute allocation
GET /api/compute/status/:request_id Check allocation status and endpoint
POST /api/compute/release/:request_id Release allocation, stop billing
// All compute endpoints require Bearer token auth
const NODEPILOT_KEY = 'np_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx';

// Request GPU compute — returns endpoint immediately
const res = await fetch('https://nodepilot-5.polsia.app/api/compute/request', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer ' + NODEPILOT_KEY
  },
  body: JSON.stringify({
    agent_id: 'your-agent-id',
    gpu: 'H100',
    vram_gb: 80,
    region: 'us-east-1'
  })
});
const { request_id, endpoint, status } = await res.json();
// { request_id: "npil_...", endpoint: "http://...", status: "allocated" }

// Poll if pending, then use the endpoint for inference
if (status === 'pending') {
  // poll /api/compute/status/{request_id} with auth header
}

// Done — release to stop billing
await fetch(`/api/compute/release/${request_id}`, {
  method: 'POST',
  headers: { 'Authorization': 'Bearer ' + NODEPILOT_KEY }
});
# All compute endpoints require Bearer token auth
import aiohttp, asyncio

NODEPILOT_KEY = 'np_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'

async def provision_gpu(agent_id, gpu="H100", vram_gb=80):
    headers = {"Authorization": f"Bearer {NODEPILOT_KEY}", "Content-Type": "application/json"}
    payload = {"agent_id": agent_id, "gpu": gpu, "vram_gb": vram_gb}
    async with aiohttp.ClientSession() as sess:
        async with sess.post(
            "https://nodepilot-5.polsia.app/api/compute/request",
            json=payload, headers=headers
        ) as resp:
            result = await resp.json()
            print(f"{result['request_id']} — {result['status']}")
            return result

result = asyncio.run(provision_gpu("my-agent", "H100", 80))
# Include your API key in every request
curl -X POST https://nodepilot-5.polsia.app/api/compute/request \n  -H "Authorization: Bearer np_xxxxxxxxxxxxxxxx" \n  -H "Content-Type: application/json" \n  -d '{"agent_id":"my-agent","gpu":"H100","vram_gb":80}'

Get your API key

Generate keys from the dashboard — view usage stats, set rate limits, revoke on demand.

SHA-256 hashed 60 req/min default Revocable

The problem

Humans built cloud infrastructure for humans.

AWS dashboards. Terraform scripts. Procurement approvals. Ticket queues for GPU allocations. Infrastructure was designed for engineers who could file a request and wait. But AI agents in 2026 don't wait. They don't file tickets. They run 24/7 and they need compute right now, priced in tokens, paid by themselves.

Cloud bills are a human problem. Compute provisioning is a human bottleneck. In an agentic world, infrastructure must be agent-native — autonomous, programmatic, and priced for machines that never sleep.

NodePilot is that infrastructure.

The future of compute

Agents that fly their own compute.

That's what autonomous AI looks like. Not just the model — the whole stack, including infrastructure.

NP