At-Bay

Businesses of every size, in every industry, are increasingly dependent on technology. For all of the benefits innovation brings, the digitization of the economy also creates risk at a magnitude never previously imagined. This new risk is complex, and it’s constantly evolving. The old way of managing risk doesn’t cut it in the digital age. We designed At-Bay from the ground up to help businesses meet digital risk head-on. By combining world-class technology with industry-leading insurance expertise, At-Bay offers clarity and confidence to businesses in the digital age. We believe that every business, big or small, when empowered to understand and manage risk, can thrive in a digital world. We address digital risk in a way that everyone, from brokers and business owners, to CISOs and CFOs, can all understand. We question, analyze, and monitor the risk of every company in our portfolio—not just once, but continuously—so we can educate, advise, and support our brokers and our insureds throughout our partnership. Because digital risk never rests, and neither do we.
Active
July 2016
187
Software
B2B
Launched

people
Roman Itskovich
CRO
people
Rotem Iram
CEO
people
Tilli Kalisky-Bannett
Managing Director

people
CEO and Advisory …
people
Mark Kraynak
General Partner, …
people
Oshri Kaplan
Board Member and …
people
Preeti Rathi
General Partner a…

$296,000,000

Series D+

$1,350,000,000

October 14, 2021
Series D+
$20,000,000

Date Announced

Round Stage

Round Size

Lead Investors

July 27, 2021
Series D
$185,000,000

Date Announced

Round Stage

Round Size

Lead Investors

December 8, 2020
Series C
$34,000,000

Date Announced

Round Stage

Round Size

Lead Investors

Acrew-Capital.png
Acrew Capital
Venture Capital
2019

Investor

Investor Type

Founded

Funds Raised

glilot
Glilot Capital Partners
Venture Capital
2011
$500,000,000

Investor

Investor Type

Founded

Funds Raised

icon-ventures.jpg
Icon Ventures
Venture Capital
2003
$780,000,000

Investor

Investor Type

Founded

Funds Raised

Artificial Intelligence, Machine Learning
3
Amazon Web Services
Hadoop, Kafka, Keras, Scikit-Learn, Spark, TensorFlow
Java, Python, Scala

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