Scan to download
BTC $66,831.28 +4.98%
ETH $1,826.85 +9.99%
BNB $625.00 +3.47%
XRP $1.28 +12.95%
SOL $75.23 +11.67%
TRX $0.3196 +0.33%
DOGE $0.0895 +3.76%
ADA $0.1874 +12.61%
BCH $225.26 +11.88%
LINK $8.48 +8.58%
HYPE $68.06 +13.72%
AAVE $75.73 +15.85%
SUI $0.8137 +8.85%
XLM $0.2276 +25.21%
ZEC $526.52 +24.51%
BTC $66,831.28 +4.98%
ETH $1,826.85 +9.99%
BNB $625.00 +3.47%
XRP $1.28 +12.95%
SOL $75.23 +11.67%
TRX $0.3196 +0.33%
DOGE $0.0895 +3.76%
ADA $0.1874 +12.61%
BCH $225.26 +11.88%
LINK $8.48 +8.58%
HYPE $68.06 +13.72%
AAVE $75.73 +15.85%
SUI $0.8137 +8.85%
XLM $0.2276 +25.21%
ZEC $526.52 +24.51%

Energy company TAR completes $27 million seed round financing to address power issues in data centers during the AI era

2026-06-15 23:37:06
Collection

Green energy infrastructure startup TAR announced the completion of a $27 million seed round financing to develop modular "plug-and-play" power systems for data centers, aimed at addressing the power and deployment bottlenecks faced by data centers in the AI era.

According to reports, the solution combines solar energy, wind energy, battery storage, and natural gas backup units to achieve nearly round-the-clock (24/7) local power supply capability, reducing reliance on the public grid and thus bypassing issues such as grid access queuing, approval delays, and power price fluctuations. TAR's co-founder stated that the core idea is to significantly compress the deployment cycle of energy systems through factory prefabrication, pre-assembly, and pre-testing, enabling data centers to achieve "rapid go-live" capability.

In pilot projects, the system can provide approximately 10 MW of stable power supply and plans to deploy over 200 MW of normal load capacity by 2027. The company noted that its first customer is an undisclosed "neocloud" service provider, aiming to provide a faster energy deployment path for AI computing infrastructure.

In terms of the economic model, TAR stated that its solution does not aim for costs below those of traditional grids but prioritizes solving the "speed issue." Its off-grid energy system can be deployed in about three months, avoiding the time costs associated with grid access and land restrictions. As the demand for AI computing continues to grow, power supply has been identified by multiple studies as one of the main bottlenecks for data center expansion. Industry analysis suggests that the "off-grid energy + modular data center" model is becoming a new direction in the competition for AI infrastructure.

app_icon
ChainCatcher Building the Web3 world with innovations.