Kao Data announces new service to quickly on-board hyperscale customers

Colocation provider readies ‘Built-to-Suit’ service to expedite the leasing process for hyperscale tenants

UK colocation provider Kao Data is launching a new service aimed squarely at hyperscale clients who want to roll out new data centre capacity at speed.

Kao Data operates a gargantuan 40MW data centre campus in North London that has scalability for a further 30MW of capacity.

Not only is the Kao Park campus one of the UK’s largest developments, it was also the first in Britain to achieve OCP-Ready status.

The state of the art facility makes it an attractive site for prospective hyperscale tenants, like Google and Amazon, companies which are increasingly turning to colocation providers for server capacity in existing facilities instead of building out new data centres themselves.

Kao Data’s new service is designed to alleviate some of the financial, contractual, logistical, and technical complexities of the colocation leasing process, which can often mar large data centre builds.

Thanks to financial support from an unnamed UK investor, the new service will offer prospective hyperscale tenants “attractive, low-cost financial terms” – the idea being that no other provider will be able to compete with Kao’s trinity of OCP-ready capacity, strategic London location and competitive costs.

In addition to funding, the service will see the provider design, build and operate capacity for hyperscale clients. In the press release announcing the launch, Kao Data cited its “award-winning expertise in customisable data centre architecture”, “optimised supply chain” and 100 percent availability.

“Developing hyperscale data centres can be costly, time consuming and complex. Our Built-to-Suit service streamlines the process and provides megawatts of readily available capacity on an already operational, planning-approved campus,” said Spencer Lamb, vice president, Kao Data.

“A key component of our bespoke approach is our ability to flex the model and incorporate the relevant components for each hyperscaler.”