Quantiphi is a category defining Applied AI and Machine Learning software and services company focused on helping organizations translate the big promise of Big Data & Machine Learning technologies into quantifiable business impact.
QDox is Quantiphi's AI-powered document processing solution accelerator. It is a deep learning-based solution powered by Amazon Web Services. QDox comes with an easy-to-use graphical interface, making it simple yet effective for business users. QDox is specifically created for State & Local Government to overcome the issues faced in extracting citizen details from different structured & unstructured documents, while simultaneously improving with constant feedback.
This 2-day workshop has been designed for Customers seeking to boost their business productivity through Generative AI capabilities with Amazon Q for Business. The workshop features interactive sessions designed to help clients familiarize themselves with Amazon Q for Business's advanced features, integration techniques, and best practices. Thereby providing a thorough understanding of how to transform business processes effectively. Learn from our best practices to get data ready and leverage GenAI to streamline workflows, and drive innovation within your organization.
Accelerate your migration from Tableau to Amazon QuickSight and unlock the power of Generative BI to make business intelligence faster, simpler, and more impactful for everyone
Supercharge your data capabilities with the Data Acceleration Program by Quantiphi and AWS. Unlock the full potential of your information and accelerate your success today with the help of our Database Acceleration Partner Program (DAPP).
Designed for the public health sector, QDox automates the processing of extensive data from patient records, laboratory reports, and research papers. The extracted information supports epidemiological studies, public health research, and informed decision-making. Gen AI enables QDox to streamline healthcare data handling, automating tasks for operational efficiency. This expedites research processes and fosters data-driven decision-making, ultimately contributing to enhanced public health outcomes. QDox for Public Health addresses how to automate dealing with a vast amount of data contained in structured & unstructured documents such as patient records, lab reports, and research papers. This extracted data can then be analyzed and used for epidemiological studies, public health research, and decision-making.
Manufacturing companies deal with large amounts of data that need to be monitored and analyzed in real-time. Quantiphi’s offering leverages Amazon Quicksight to help visualize this data in the form of dashboards, making it easy to understand and act upon.
This offering will allow users to optimize their Amazon Q in the Connect Deployment Journey. From initial consulting to continuous enhancement, our offering ensures that your contact center is equipped with a powerful AI-driven assistant that improves agent productivity and compliance, and fosters a better customer and agent experience. Our customization options allow us to tailor the AI’s functionality to fit your specific business needs and workflows, ensuring that the integration aligns seamlessly with your existing processes.
Transform your data analytics and visualization capabilities with Quantiphi's Generative AI Insights Workshop, leveraging Amazon Q in Amazon QuickSight. This 2 day workshop empowers organizations to harness generative AI for enhanced data visualization and decision-making, providing actionable insights in a fraction of time. Join us on this immersive journey to embrace the full potential of Generative AI on AWS to drive growth and success unique to your business needs.
Revolutionize your credit scoring approach by harnessing Quantiphi's ML-powered Credit Scoring Platform, which blends conventional and unconventional data sources for precise risk profiling.
Quantiphi offers a powerful machine-learning model designed to accurately predict customer churn and provide actionable insights to reduce attrition rates. The model analyzes customer behavior and assigns churn probability scores to both new and existing users, including those with multiple accounts. By leveraging feature engineering through Exploratory Data Analysis, the model identifies interpretable reasons and patterns contributing to customer churn.
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