Intelligent AI, a property risk analytics provider, has announced its expansion into the US market following its selection for the Connecticut InsurTech Corridor.
The move marks a key milestone for the company as it builds on momentum in the London market and responds to growing demand from insurers seeking better data quality, improved underwriting precision and stronger portfolio resilience.
Many insurers continue to face persistent data challenges during the underwriting process. According to Intelligent AI, 40–50% of insurance submissions still arrive incomplete, while underwriters spend more than half their time gathering missing information rather than assessing risk.
These challenges are particularly acute for large and complex property portfolios, where inconsistent or outdated data can materially affect pricing accuracy and exposure management.
Intelligent AI aims to address these issues by providing high-resolution COPE intelligence – Construction, Occupancy, Protection and Exposure – alongside rebuild cost analytics. The platform gives insurers a structured and consistent view of property risk at the point of underwriting decision.
This approach enables faster underwriting, improved risk selection and more accurate pricing across the policy lifecycle.
Anthony Peake, CEO of Intelligent AI, said, “Expanding into the US is a natural next step for Intelligent AI, and being selected for the Connecticut InsurTech Corridor gives us a powerful platform to engage directly with leading US insurers.
“The data challenges we’ve solved in the London market are just as relevant in the US. Insurers who fix the data problem first will win the best risks, improve loss ratios and build more resilient portfolios.”
Intelligent AI’s API-first, cloud-ready platform integrates directly into insurer workflows, supporting underwriting, claims management and portfolio analytics.
By expanding into the US, the company aims to help insurers improve submission quality, reduce underinsurance risks and strengthen catastrophe exposure modelling across property portfolios.
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