At Tensorflight, we firmly believe that AI-based solution has the potential to transcend boundaries and transform the insurance industry. Our diverse array of use cases reflects our unwavering dedication to creating smarter, more efficient, and profoundly impactful solutions.
At Tensorflight, we’re passionate about leveraging cutting-edge technology to transform the landscape of property inspections and underwriting. Our collaboration with QBE, a leading global insurer, exemplifies this commitment.
Working alongside QBE, we embarked on a mission to revolutionize property inspections for QBE’s UK portfolio. Our AI-driven solutions empowered QBE to identify and filter buildings with specific characteristics, like buildings above a certain height with external cladding across their UK Property portfolio in just 24 hours. This saved QBE weeks of laborious work while ensuring a level of accuracy that’s second to none.
But our journey doesn’t stop here. We’re proud to continue our partnership with QBE underwriters and modelers, relentlessly pushing the boundaries of what’s possible. Together, we are continuing to explore smarter ways to complete, validate, and enrich property schedule data like never before.
By harnessing our advanced technology, we’re aiding the Kyiv School of Economics in evaluating the extent of the damage and facilitating a path toward recovery. This initiative isn’t just about innovation; it’s about using our expertise to make a meaningful difference in communities. Our dedication to societal impact drives us to extend our capabilities beyond the business realm and into the realm of positive change.
At Tensorflight, we believe that technology should not only revolutionize industries but also serve the greater good. As part of this commitment, we’ve joined hands with the Kyiv School of Economics to make a positive impact on Ukrainian cities. Our collaborative project focuses on assessing the damage inflicted upon critical infrastructure in Ukrainian cities.
At Tensorflight, we understand the critical importance of accurate replacement cost data in the insurance industry.
Our partnership with PZU, a leading insurance provider, exemplifies our commitment to solving the under-insurance problem. We are proud to collaborate with PZU, offering them our cutting-edge replacement cost data for small and mid-market commercial properties.
Through this collaboration, we assist PZU in identifying undervalued properties and ensuring precise coverage assessments. This strategic partnership not only enhances operational efficiency but also bolsters the overall integrity of the insurance ecosystem.
At Tensorflight, we’re dedicated to advancing property underwriting through innovative partnerships. Our latest collaboration with Munich Re, a global leader in risk management and insurance solutions, is poised to redefine SME underwriting in Europe.
Focusing initially on the vibrant market of France, our joint project with Munich Re involves the integration of vital building attributes, including occupancy type, number of stories, and COPE (Construction, Occupancy, Protection, and Exposure) data, into the ‘flowin’ platform. This infusion of precise data empowers underwriters to make informed decisions with confidence. Our ambitious journey is just beginning.
As we mark our successful entry into France, we’re excited to announce our plans to expand our reach to other Western European countries in the coming year. Together with Munich Re, we aim to shape the future of SME underwriting across the continent.
At Tensorflight, we recognize the power of data to transform the way businesses operate. Through our partnership with MS Amlin Business Services, we’re indirectly saving users valuable time while providing them with invaluable insights.
Our data seamlessly integrates with MS Amlin’s machine learning model, enhancing their ability to assess risk factors when pricing cargo storage policies. This data plays a pivotal role in our machine learning model, enabling a comprehensive understanding of the critical variables that influence the likelihood of a fire incident at a property within the next year.
By combining Tensorflight’s data with advanced data analytics tools developed within the LDH, users gain a holistic view of potential hazards across their U.S. property portfolio. This collaborative effort empowers data-driven decisions and facilitates a well-rounded approach to risk assessment.
“A pilot that provided information on about 3 000 schools has so far saved Zurich about 500 hours in manual work. Most of the schools, for ages five to 16 years, have more than one building, and Tensorflight’s technology is being rolled out to – in total – about 20 000 schools across the UK. That’s about 50 000 buildings. This could ultimately lead to thousands of hours of effort saved”.
Mark Budd – Head of Innovation, UK, Zurich Insurance Group
