Aravolta
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For lenders and asset-backed financing

Verify every GPU behind the loan.
Out of band, with no agents.

One Aravolta node reads every financed server from its BMC, with nothing installed on the borrower's machines. Serial numbers for each server and GPU, live telemetry, and location checks show the collateral is there, running, and where the loan says it is.

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“Aravolta bridged the gap between our risk requirements and the technical reality of the data center...”
Conor Moore
Co-Founder & COO, USD.AI
Live demo
Sample data. At onboarding the node finds each server's BMC and reads it over Redfish and IPMI.
Loan 2041-B collateral

site-12 · 16 servers · 128 GPUs

No alerts firing
AssetSerialHealth
gpu-node-05SQFGYE40ZOK
gpu-node-06SR2F8TSZWOK
gpu-node-07SSPDJ5FZUOK
gpu-node-08STACUH3ZSOK
gpu-node-09SUXA4WRYQOK

gpu-node-07 / GPU 5

GPU 5OK

H100 80GB HBM3

55°C

State

Enabled

Slot

4

NameGPU_SXM_5
Serial1654475187233
HealthOK

The other seven GPUs in gpu-node-07 report OK.

Case study · USD.AI

Verifying GPU-backed credit positions

How a GPU financing company uses Aravolta to verify the assets behind its credit positions and underwrite on telemetry.

Read the case study
Bare metal loans

Verified at the hardware, not on paper

The node on site reads each server's management controller, never its operating system. That gives a lender four checks on every server behind the loan.

gpu-node-07 / Overview
System Information

Basic hardware and configuration details

Model8-GPU Server
SKUGS8-H100
Serial NumberSSPDJ5FZU
Firmware Version7.10.30.00

Sample data. The System Information card of one server's Redfish profile.

Serial numbers, read out of band
The node reads the serial number, model, SKU, and firmware of every server and GPU from its BMC over Redfish or IPMI. Checked against the loan's collateral schedule, a swapped or missing GPU shows up.
Location that can't be spoofed
Aravolta's location algorithms, with optional GPS on the node, verify where the GPUs are. A lender can confirm the collateral is where the loan says it is and has not been moved to a sanctioned country.
Telemetry on bare metal
Live GPU temperature, power, and utilization show the collateral is installed and running. A GPU that stops reporting raises an alert.
No agents
Nothing is installed on the borrower's servers or operating system. Everything is read out of band from the BMC, so there is no access to workloads or data.
Per asset, from the hardware

What the telemetry gives an underwriter

Per-asset data on the collateral, from deployment through retirement.

Redfish Reports / Preview Extracted Metrics
Extracted Metrics

#2104gpu-node-04

LabelValue
GPU (Slot 1) GPUUsage97.00%
GPU (Slot 1) PrimaryGPUTemperature76.00 °C
GPU (Slot 1) PowerConsumption684.21 W
GPU (Slot 1) GPUMemoryUsage71.00%

Sample data. The GPU metrics a server's BMC reports over Redfish, one row per GPU and metric.

Structures

Financing structures we support

Each term references a number the lender can verify.

Sale-leasebacks with performance triggers

Lease terms that move with measured utilization and thermal performance. If the telemetry shows the assets are being overworked, a maintenance reserve or early buyback clause triggers on its own.

Example

A 5-year sale-leaseback with a quarterly payment adjustment based on average GPU utilization and thermal violations.

Usage-based credit lines

Revolving facilities where capacity and rate are tied to measured GPU-hours. Payments follow verified compute output rather than an estimate from the borrower.

Example

A credit line where the rate steps down for operators that keep GPUs at 60 to 75% utilization.

Portfolio risk monitoring

For lenders holding several GPU-backed loans: asset performance, utilization variance, and depreciation trend, rolled up across every deal.

Example

A dashboard that shows which borrowers run their GPUs hot and which run them conservatively, with the projected salvage value adjustment for each.

Lifecycle

One record per asset, from deployment to retirement

Aravolta follows each GPU from the day it enters service to the day it is retired. The depreciation curve is built from that asset's measured usage rather than an industry table.

  1. 1

    Deployment and baseline

    One Aravolta node on the management network finds every device and imports it, with no asset spreadsheet and no agents on the servers. Each GPU goes on record with its serial, slot, and starting temperatures. The assets of a new deal are under monitoring in 2 to 4 weeks.

  2. 2

    Ongoing monitoring

    Every financed device is read continuously and checked against its baseline. An alert fires when an asset drifts from the assumptions the loan terms rest on.

  3. 3

    Depreciation and salvage value

    Each asset gets its own depreciation curve from measured wear and performance decay. The salvage value projection updates as the asset ages.

Talk through your portfolio

Bring the deal and the asset list. We will show what the telemetry looks like for that collateral and how it maps to your covenants.

  • Asset monitoring across the portfolio
  • Depreciation models per asset
  • Automated compliance reporting
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