The Energy Intelligence Platform for AI Datacenters.
Joined April 2026
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Ziani Systems retweeted
Thank you, @arm!
Our @ZianiSystems integration with Arm Neoverse happened because of the people at Arm who worked with us on it. We’re now working on the Arm AGI CPU, and we’re excited to share those results as well. Stay tuned!
Ziani Systems retweeted
More detail on the Bentaus side of the @Synota_ partnership:
@ZianiSystems was built to read power in real time. Modulating GPU load against grid dispatch signals only works if the orchestration layer knows actual draw as it happens, which is why the control loop includes a telemetry and validation stage that confirms execution before anything gets reported back to the grid.
That same telemetry is what the settlement framework will draw on. Ziani supplies the measurement of what the infrastructure actually consumed. Synota supplies the billing and settlement technology that connects that measurement to customer commercial terms.
The framework is being designed to cover GPU, CPU, token, energy and AI storage usage, with daily and monthly settlement first.
First deployment is targeted for Q4 2026 on Bentaus infrastructure.
Ziani Systems retweeted
How do you get a GPU running AI inference to respond to the grid?
One integrated loop: ERCOT conditions → Luxor's QSE signal → @ZianiSystems orchestration → GPU curtails to ~25%. Under half a second, no lost work.
The full picture 👇
Ziani Systems retweeted
How do you get a GPU running AI inference to respond to the grid? Check out how we worked with @luxor using our @ZianiSystems
How do you get a GPU running AI inference to respond to the grid?
One integrated loop: ERCOT conditions → Luxor's QSE signal → @ZianiSystems orchestration → GPU curtails to ~25%. Under half a second, no lost work.
The full picture 👇
Ziani Systems retweeted
First response of an AI inference GPU to a live @ERCOT_ISO 4CP signal.
@luxor Energy's QSE generated the curtailment signal. @ZianiSystems by @BentausOfficial took the GPU from full draw to roughly 25% in under 500 milliseconds, closed loop and verified, with inference workloads checkpointed, paused, and resumed. Nothing dropped.
Four fifteen minute peaks set a large share of a Texas data center's annual transmission bill. Now AI load can respond to them. ERS enrollment next.
prnewswire.com/news-releases…
Ziani Systems retweeted
Luxor Energy, the energy division of @luxor and @BentausOfficial report that their Ziani platform cut a live GPU's power draw to 25% of normal in under 500 milliseconds, while inference workloads kept running. It's the first demonstrated AI GPU response to an ERCOT 4CP signal.
Why it matters: ERCOT's Four Coincident Peak program rewards large loads that pull back during the grid's highest demand intervals each summer (June through September). Until now, AI data centers have largely sat outside that conversation as fixed, inflexible load. This result suggests that doesn't have to be the case. GPU fleets could become active participants in market programs, not just consumers of power, with real potential to lower transmission costs.
Congrats to the Luxor Energy and Bentaus teams on a genuinely useful proof point for grid-aware AI infrastructure.
luxor.tech/news/corporate-ne…
Ziani Systems retweeted
Day 1 in Hamburg is officially under way.
Today, @Supermicro opened BoothB10 at ISC High Performance, and the newest version of SuperCloud Composer is live with our @ZianiSystems Systems' GPU Flex built in for the first time.
This is what months of engineering, testing, and partnership with Supermicro look like when it reaches the floor. We are sharing a few photos of Galyn Black and Jeremy Swyers from the event today.
If you are at ISC 2026, you know where to find them.
If you are not, follow along here as we share what happens next.
Hamburg. #ISC2026
