Artificial Inteligence Insurance Machine Learning Marketing 
CIO
FEBRUARY 6, 2023
The insurance industry is undergoing a sea change, with IT playing a crucial role in rolling out digital customer experiences for policyholders and agents, as in-person meetings all but vanish in the post-pandemic era. IT as industry differentiator Insurers and financial services firms like MassMutual, of Springfield, Mass.,
TechCrunch
JANUARY 7, 2022
The company creates optical sensors and novel classification systems based on machine learning algorithms to identify and track insects in real time. That data is turned into audio and analyzed by machine learning algorithms in the cloud. The key here: real-time information. Risk can keep people poor.
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TechCrunch
JANUARY 9, 2023
Superscript , an insurance broker and tech platform targeting SMEs and “high-growth” tech firms, has raised £45 million ($54 million) in a Series B round of funding. Founded out of London in 2015, Superscript constitutes two core insurance businesses: an online-only “self-serve” platform that’s available to U.K.
Coforge
AUGUST 27, 2020
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TechCrunch
APRIL 12, 2022
Processing claims at scale presents a challenge for insurers, particularly where the claims entail factors like complex underlying health conditions. A growing cohort of startups including Alan, Tractable and Snapsheet offer tools to help customers navigate through the insurance claims process. ” Accelerating insurance claims.
Hacker Earth Developers Blog
MAY 22, 2020
In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. Again, focus on Data Science and Machine Learning.
Altexsoft
JULY 23, 2020
When speaking of machine learning, we typically discuss data preparation or model building. The fusion of terms “machine learning” and “operations”, MLOps is a set of methods to automate the lifecycle of machine learning algorithms in production — from initial model training to deployment to retraining against new data.
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