Drive innovation, better assess risk, deliver accurate quotes fast, and delight your customers by improving the quality of your AI/ML, automation, and big data analytics tools.
Insurance decision-making is becoming fully digitized. But to get there, you must feed many disparate data sources into your big data analytic engines and AI/ML models.
Quickly develop and improve your AI/ML models to bring your solutions to market faster and gain competitive advantage.
Rapidly unlock the value of disparate sources of structured and unstructured data by digitizing, verifying, cleansing, and annotating it.
Eliminate bottlenecks, speed up turnaround times, and improve SLAs for your underwriting and claims processing functions.
Free your data scientists to focus on higher value work, invest in computer vision, and discover new data insights.
Our skilled data analysts and project managers keep open lines of communication with you and become an extension of your team.
Since early 2021, CloudFactory has been helping Carpe Data validate the business data we use to train our AI - work that’s core to our company because our global insurance carrier clients rely on us for deeper insights into risks. We value many things about our partnership with CloudFactory, but especially the continuity of the team, transparent communication, and how the team scales while delivering high-quality work on time.
Matt McLaughlin
Vice President, Data Strategy & Management
Quickly scale as your needs change without sacrificing data quality or slowing down projects by using our vetted, managed teams.
Let our experience guide you to unlock the value of data, bring new solutions to market, optimize operations, and win in your space.
Do your end users directly engage with your AI systems? Will they engage? Then ethics, and how you apply them, are crucial.
This insurance company expanded its business with the help of a dedicated data analyst team that handles upfront data processing.
Humans in the loop can make or break AI success. Apply people strategically to improve data quality and accelerate the AI lifecycle.
