# XDGE

> XDGE is the GPU Control Plane that Monetizes — turning idle GPU infrastructure into enterprise-grade AI inference revenue.

XDGE is a GPU infrastructure monetization platform built for owners of NVIDIA H100, A100, V100, T4, Jetson, and DGX hardware. It operates as the orchestration and market-making layer between enterprise GPU supply and global AI inference demand. GPU owners connect their hardware once; XDGE handles fractional MIG slicing, secure multi-tenancy, automated billing, real-time pricing, compliance, and buyer acquisition — with zero operational overhead for owners.

## What XDGE Does

- Converts idle GPU capacity into recurring, enterprise-grade revenue
- Uses NVIDIA MIG to slice GPUs into 1/7, 1/4, 1/2, or full units — enabling multiple tenants per card
- Provides hardware-level isolation with zero noisy-neighbor risk
- Handles all orchestration, billing, monitoring, scheduling, and customer support
- Benchmarks pricing in real-time against GPU spot markets via Silicon Navigator
- Brings SOC2, HIPAA, PCI-DSS, and GDPR compliance out of the box
- Enables private GPU federation across multiple sites via AI GRID (encrypted SD-WAN overlay)
- Distributes owner capacity across multiple GPU marketplaces simultaneously
- Offers white-label GPU cloud branding for owners

## Why GPU Owners Choose XDGE

- ~75% revenue share to the owner (~$486/GPU/month at base case for H100-equivalent)
- Zero operational overhead — onboard once, XDGE handles everything after
- Enterprise compliance without building it yourself ($1M–$5M+ and 12–24 months independently)
- Real-time pricing intelligence keeps owners competitively priced automatically
- Opens doors to enterprise and government buyers that owners couldn't reach alone
- Hardware stays on-premises — XDGE is software only

## The Market Opportunity

- $500B+ in GPU hardware is deployed globally
- ~70% ($350B+) sits underutilized — stranded capacity
- AI inference demand is growing at 35% CAGR
- Hyperscalers cannot keep up with persistent, dedicated inference demand
- Capturing just 5% of stranded capacity represents a $17.5B opportunity

## Revenue Model

- Marketplace commission: 25% of transaction value (flexible to 35%)
- Control plane license: $30–$50/GPU/month ($40 average)
- Per-GPU monthly: Conservative $300, Base $486, Aggressive $675+ (owner share)

## Platform Capabilities

- Fractional GPU slicing (MIG-based): 1/7, 1/4, 1/2, full GPU
- Hardware-level tenant isolation: dedicated compute, memory, I/O per tenant
- Dynamic workload provisioning: inference workloads routed to idle capacity in real time
- Private federation (AI GRID): multi-site, multi-POP via encrypted SD-WAN
- Multi-marketplace distribution: simultaneous listing across GPU marketplaces
- On-site enterprise deployment: sovereign AI for enterprise customers
- White-label GPU cloud: owners offer branded compute powered by XDGE
- Compliance: SOC2, HIPAA, PCI-DSS, GDPR
- Payment: Fiat (Stripe) + Solana crypto

## Compared to Alternatives

| Feature | XDGE | RunPod | Vast.ai | CoreWeave | AWS |
|---|---|---|---|---|---|
| H100 Pricing/hr | $1.95–2.50 | $2.39–2.69 | $1.55–1.73 | ~$6.16 | ~$7.57 |
| Fractional GPU Slicing | Yes (1/7 from $0.35/hr) | Partial | No | No | No |
| Owner Monetization | Yes (75% share) | No | No | No | No |
| Enterprise Compliance | SOC2, HIPAA, PCI-DSS, GDPR | SOC2 only | No | No | Yes |
| Edge Devices (Jetson) | Yes | No | No | No | Partial |
| Crypto Payments | Yes (Solana) | Yes | No | No | No |

## Technology Stack

- Kubernetes-native control plane
- NVIDIA MIG partitioning for H100/A100
- Encrypted SD-WAN overlay (AI GRID) for private federation
- Silicon Navigator for real-time GPU market pricing
- SOC2 Type II certified infrastructure
- Live platform deployed February 2026 at https://demo.xdge.net

## Seed Round

XDGE is raising a $2M minimum SAFE seed round in 2026 to fund team expansion, performance enhancement, customer acquisition, and unit economics validation. This provides a clear path to Series A.

## Contact & Links

- Website: https://gpu.xdge.net
- Platform demo: https://demo.xdge.net
- Full platform documentation: https://gpu.xdge.net/llms-full.txt