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The financial risk layer for AI infrastructure

A steadier cost
of intelligence.

Model the power and compute price exposure underneath your fleet, and hedge it before it reaches your P&L.

Electricity infrastructure on the left and GPU servers on the right, connected through Vasuki’s risk layer.
V A S U K IThe risk layer
Map → Structure → Hedge → Monitor
A continuous left-to-right flow passes from the electricity grid through Vasuki to compute. Smooth disturbances settle through the risk layer. Separate charts show the price volatility of each market.
Follow the exposure
01The exposure

The risk is in
the mismatch.

Volatility in power prices and compute revenue squeezes margins. Financing becomes tougher.

Power costs rise first. Compute revenue falls later. The horizontal axis is time. The vertical axis is dollars per GPU-hour, increasing upwards. At fixed utilisation, compute revenue and the allocated electricity cost are initially fixed. The power contract resets first and electricity cost steps up, while customer revenue stays fixed. Later, the customer contract renews at a lower compute rate and revenue steps down. The shaded gap, labelled margins, is revenue less power cost; it narrows at both events and excludes other operating and capital costs. This is an illustrative scenario, not a forecast.
Illustrative, at fixed utilisation. Power cost allocated per GPU-hour; other operating and capital costs excluded.
02Inside the risk layer

From exposure
to action.

  1. 01Map

    Understand what you pay, what you earn and when each contract changes.

  2. 02Structure

    Compare hedge options, their cost and the risks they leave uncovered.

  3. 03Hedge

    Coordinate the agreed hedge where suitable instruments and counterparties are available.

  4. 04Monitor

    Track what the hedge covers as prices, usage and contracts change.

Built for

  • Neoclouds
  • Data centres & colos
  • Power producers & utilities
  • The lenders behind them