From grid strain to grid strength.

We transform AI data centers into resources the grid can count on. AionLink lets AI data centers and crypto-mining facilities cut their power draw the instant the grid is stressed — without disrupting the workloads inside. Proven on real GPU clusters, not simulations.

Grid fault, with and without AionLink AionLink Grid voltage voltage sag Facility load load surge controlled load shed (SLA preservation prioritized)
Same grid fault, two outcomes. An unmanaged facility surges against a stressed grid. An AionLink-managed facility sheds load in a controlled way, stays connected, and keeps its service commitments.

Tokens from stranded electrons

STRANDED ELECTRONS → AIONLINK → TOKENS

The grid wastes enormous amounts of energy it cannot place — while AI compute waits years for power it cannot get. These are the same problem, unsolved in both directions.

AionLink closes the loop at the layer where the load actually lives: a data center that senses grid stress and responds on its own, in milliseconds, keeping its AI workloads intact while it holds the grid steady. Stranded electrons become intelligence, and the grid's largest new load becomes one of its most dependable participants. AionLink is the link.

Today, one facility. The same intelligence extends to coordinated fleets — many sites acting together as one dependable resource for the grid.

Why it matters now

This is no longer one state's experiment — a national consensus is forming. In Texas, ERCOT's new rules make ride-through capability a condition of connecting, and facilities that can't demonstrate it wait longer in the queue. NERC has elevated large-load ride-through to a Level 3 alert — its most serious tier — after data-center-driven disturbances. In PJM, surging data center demand has already triggered emergency federal action, and FERC is directing reforms to how large loads connect to the grid. Every authority is converging on the same conclusion: data centers must become grid participants, not just grid customers. AionLink is the demand-side solution that bridges the gap — solving the voltage ride-through and grid-strain problems from the data center's perspective, at the layer where the load actually lives. Not a retrofit bolted on from the outside, and not a central controller bolted on from above: a first-principles solution that lives in the load itself, and it has arrived.

Measured on real hardware

Same sag, two outcomes. Current drawn by the facility as grid voltage falls.
1.00.90.80.70.60.50.40.35 0.00.51.01.52.02.5 retained voltage (pu) — deeper sag → facility current (× normal) 150% limit — NOGRR282 §2.15 compliant region below unmanaged crosses 150% at 0.667 pu unmanaged load — current exceeds the limit AionLink — current held at or below the limit
As voltage falls, a constant-power load draws more current. Unmanaged, it crosses the 150% ceiling on a shallow sag. AionLink reduces power so current stays within the limit into deep-sag territory. Representative of results measured on production NVIDIA GPU clusters; sealed traces available under NDA.
40%+

Instant power reduction during grid fault events, measured on production NVIDIA GPU clusters running live AI workloads.

~2%

Impact on AI services. Customer-facing inference stays within normal bounds while the facility responds.

0

Disconnections across repeated, back-to-back grid disturbances — the failure mode new rules are written against.

Every result is cryptographically sealed and verifiable. Independent professional-engineer validation is in progress. Detailed evidence available under NDA.

From surviving the fault to serving the grid

Three capabilities, one facility. Each rung builds on the one below it.

  1. available today

    Voltage ride-through

    When the grid sags, an AionLink facility cuts load in milliseconds and stays connected, the failure mode the new rules are written against. Proven on production NVIDIA GPU clusters and cryptographically sealed.

    See the evidence →
  2. grid participation

    Demand response and PCLR headroom

    Beyond fault survival, an AionLink facility flexes on grid signals — reducing during stress, and using its full permitted headroom when the grid is calm.

    Grid stresssignal AionLink sensesat the facility Facilityreduces load Workload moves to asite with headroom Grid seesrelief
  3. fleet

    Matched state migration

    When one site must curtail, its live workload moves to another facility with headroom and resumes intact — turning a fleet of sites into one dispatchable resource. This is what makes participation in programs like ERCOT's PCLR practical: load can leave a stressed node without stopping work.

Operating or developing AI infrastructure?

If grid rules, interconnection timelines, or power flexibility are on your roadmap, we should talk. Briefings are confidential and technical.

info@aiontracks.com