Improve Business Outcomes with Machine Learning

Solve your most common business challenges with practical machine learning use cases

From enhancing customer experiences and boosting employee productivity to cutting costs and reducing fraud, machine learning can help you deliver on your business objectives and propel your digital transformation. Yet, finding the right place to start to apply machine learning can be difficult. Implementing practical, proven machine learning use cases can help to remove this barrier for your organization and quickly provide real business impact.

Whether you have a specific business outcome in mind or you are just exploring, you can accelerate your machine learning journey by starting with one of the following use cases.

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Add intelligence to your contact center

Enhance your customer service experience and reduce costs by integrating machine learning into your contact center. Through intelligent chat and voice bots, voice sentiment analysis, live-call analytics and agent assist, post-call analytics, and more, personalize every customer interaction and improve overall customer satisfaction.

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Automate data extraction and analysis

Instantly extract text and data from virtually any document such as loan applications and medical forms without manual effort. Process millions of pages in hours, uncover valuable insights, and implement human reviews with intelligent document processing.

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Boost employee productivity and customer satisfaction by delivering accurate and useful information to employees, customers, and partners quickly. Help users get answers faster from siloed and unstructured information sources across the organization by using intelligent search.

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Streamline self-service processes with Conversational AI

Enable omnichannel, 365/24/7 communication with your customers in engaging ways through chatbots, voice assistants, and interactive information kiosks. Increase user satisfaction, reduce operational costs, and streamline business processes.

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Personalize customer recommendations

Improve customer engagement and conversion by creating personalized web experiences—tailored to individual customer preferences and behaviors across channels—through recommendations, curated content, and targeted marketing promotions.

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Identify fraudulent online activities

Improve profitability by automating the detection of potentially fraudulent online activity, such as payment fraud and fake accounts, using machine learning and your own unique data

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Streamline content moderation operations

Streamline workflows or automate them entirely with AI to create safe online environments and minimize moderation costs. Enable multi-modal capabilities, such as text, image, video, and audio moderation. Decide where to integrate human moderators and Natural Language Processing (NLP) technology.

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Analyze media content and discover insights

Create new insights from video, audio, images and text by applying machine learning to better manage and analyze content. Automate key functions of the media workflow to accelerate the search and discovery, content localization, compliance, monetization, and more.

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Add AI capabilities to your business analytics

Accurately forecast sales, financial, and demand data to streamline decision-making. Automatically identify anomalies in your business metrics and their root cause to stay ahead of the game.

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Improve developer operations with intelligent insights

Detect deviation from best practices and other common coding bugs and maintain a high-quality customer experience by reducing deployment risks and facilitating faster delivery of new features. Empower developers to evaluate operational data and leverage intelligent insights to reduce the time and effort spent analyzing and resolving issues.

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Modernize your machine learning development

Accelerate innovation while reducing cost by modernizing machine learning development lifecycle through scalable infrastructure, integrated tooling, healthy practices for responsible machine learning use, tool choices accessible to developers of all skill levels, and efficient resource management.

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Industries

Deliver better personalized experiences

Healthcare and life sciences

Unlock hidden potential in your health data with HIPAA-eligible ML—for petabyte-scale analysis and fast unstructured text and speech documentation.

Learn more: ML for Healthcare

Increase customer engagement

Industrial and manufacturing

Detect abnormal machine behavior, spot defects, enable predictive maintenance, and improve operations with purpose-built Industrial AI services—no ML experience required.

Learn more: ML for Industrial

Personalize every touchpoint

Financial services

Innovate with ML across banking, payments, capital markets, and insurance sectors to improve customer experience with personalization, and virtual assistants and prevent online fraud.

Learn more: ML for Financial Services

Customer spotlight

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  • 3M
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    3M, a Minnesota-based multinational corporation that produces adhesives, medical products, and more, uses Amazon Kendra to help its scientists find the information they need by handling natural language queries quickly and accurately. 

  • Subway
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    The Subway restaurant chain used AWS personalization solutions to quickly deliver personalized recommendations for their endless varieties of ingredients and flavors to fit the unique lifestyles of their guests.

  • Change Healthcare
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    Change Healthcare, a leading independent healthcare technology company, used AWS data extraction and analysis solutions to unlock information from millions of documents, creating more value for patients, payers, and providers.

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Move beyond the hype and into the real world of machine learning. In this eBook, 7 Leading Machine Learning Use Cases, we have outlined the leading use cases where businesses have successfully applied machine learning to achieve fast, efficient, measurable results.