Lyrah builds silicon carbide solid state transformers that convert grid medium voltage straight to 800V DC — one stage instead of five. 98.5% efficient, 70% smaller, and on site in 16 weeks instead of two years.
Rack density jumped from 5–15kW to 120kW–1MW in a single hardware generation, while the equipment that feeds those racks is still built the way it was in 1960. Data centers are being finished and sitting dark, waiting on electricity.
NVIDIA Blackwell-class racks draw 120kW to 1MW each. The distribution gear in front of them was specified for a tenth of that.
Conventional transformers ship in 80–100 weeks. AI compute demand grows 10× every two to three years. The math does not work.
US data center power infrastructure alone is short tens of billions of dollars of deliverable capacity.
Finished facilities sit idle because interconnection and equipment can't arrive on the same timeline as the servers.
Our solid state transformer collapses the entire legacy conversion chain into a single modular, liquid-cooled cabinet — and adds protection, control and grid services that a passive iron-core transformer can never provide.
| Metric | Traditional | Lyrah SST |
|---|---|---|
| Deployment lead time | 80–100 weeks | 16 weeks |
| Footprint | 29 m² per MW | 70% smaller |
| Efficiency | 93.6% | 98.5%+ |
| Fault protection | Mechanical, > 10 ms | Fast protection |
| Scalability | Monolithic | Modular, seamless expansion |
Factory-integrated cabinet arrives ready to energize. No multi-trade site build-out.
Reclaim the 30–50% of floor area currently consumed by electrical rooms.
Roughly five points of efficiency straight off the utility bill, every hour, for 25 years.
Modular redundancy and fast isolation keep the load up through faults.
Silicon carbide switching in the tens of kilohertz shrinks the magnetics by 90%. What used to be a 60Hz iron core the size of a shipping container becomes multiple high-frequency transformers inside a cabinet — with three defensible technologies wrapped around it.
An isolation barrier with no partial discharge pathway, giving a service life measured against the building rather than the warranty.
The unit is an active grid asset, not a passive load. Black start, islanding and voltage support turn your power infrastructure into an ancillary-services revenue line.
Liquid cooling pulls heat out five times faster than air, so each SiC die does twice the work it otherwise could.
Built on the high-volume EV traction supply chain — proven reliability, real cost curves, and capacity that already exists.
Prototype hardware complete: power modules, protection and controls integrated into a single 35kV-to-800V data center power supply unit.
Engineering toward UL 3400 and UL 1741 for commercial deployment in North America.
The efficiency gain pays for itself. The space you get back is what actually changes the business case — 70% less footprint is roughly 250 square feet returned to the floor, which is about ten more GPU racks earning revenue.
less electrical footprint per megawatt
AI power demand roughly doubles by 2030, from about 11GW to 21GW, while the industry converges on 800V DC distribution and efficiency mandates tighten. The solid state transformer market across data centers, EV charging and grid applications reaches $15–25B by the end of the decade.
Nearly doubling by 2030 as training and inference build-outs compound.
Rack-level DC distribution is becoming the reference architecture for high-density AI.
80–100 week transformer queues make speed of delivery a purchasing decision by itself.
ESG commitments and utility interconnection limits both reward every point of efficiency.
Hyperscale operators and AI cloud providers building high-density compute, where footprint, efficiency and time to energization all decide the economics of a site.
Grid-scale storage, where medium-voltage conversion and grid-forming control let an installation provide ancillary services rather than only shifting energy.
Market sizing and performance figures reflect Lyrah's internal modeling and prototype testing. Production specifications are confirmed per project.
We work with data center developers, colocation providers and AI infrastructure teams on 5–7MW deployments. Tell us about your site and load profile.