Amazon Kendra Customers

Today's leading companies trust Twilio's Customer Engagement Platform used by hundreds of thousands of businesses and more than ten million developers worldwide to build unique, personalized experiences for their customers. To keep up with the growing demand of customer support, we set out to deliver an intelligent search and ticket submission flow that deflects tickets and reduces costs, while improving the overall customer experience. Unlike a traditional search engine, Amazon Kendra allows us to extract the specific segment of text with any article that has the recommended answer to a customer query.  Amazon Kendra enabled us to deflect tickets with a high rate of success.

One of our strengths is the experience and knowledge we have gained in designing data-driven corporate management in a wide variety of fields. Effectively leveraging these information assets to create synergies is a key role in enhancing the quality of our solutions. Amazon Kendra is a strong support platform for this role. Since Amazon Kendra allows us to retrieve information distributed across multiple internal platforms, such as Wiki and document files, from a common interface, the flexibility of our information assets has been dramatically improved since its deployments. It was also easy to implement chatbots integrated with AWS Lambda, and providing the chatbots played an important role in spreading the search mechanism within the company. We believe that we will be able to continuously improve our technical capabilities and the quality of our solutions by making effective use of Amazon Kendra's powerful features.

Using the right search solution to power RIA was critical as we wanted to eliminate the time-consuming and exhausting process that our customers followed to find information. To address this problem, we turned to Amazon Kendra, a powerful AI solution that quickly and accurately handles Vivpro's innovative data model and allows natural language queries. With Kendra, pharma and biotech researchers can now find the information they need much faster, collaborate more effectively, and accelerate the development of novel medicines. Their time spent in finding information has reduced by 60%-90% leading to improved productivity. Amazon Kendra's solution and collaboration has been invaluable to Vivpro's success to bring unified biointelligence platform and innovative services to make evidence-based clinical, regulatory, and business decisions at lightning speed for pharmaceutical, biotech, device developers, CROs, and investors.

Orion Health is a longtime partner of AWS, so it was natural for us to look to Amazon Kendra search for our Digital Front Door solution. Kendras' rapid six-week prototyping accelerated time to value on the project. And its ability to enable natural language searches on disparate, federated data sets was critical to reduce the noise typically with search engines.

At 3M, science is at the heart of everything we do. For us, R&D is the heartbeat of 3M; we invest deeply into the science that makes 3M strong. That investment is the key that enables us to introduce over 1200 new products every year. When our material scientists lead new research, they need access to information from prior relevant research—information that’s buried in the many patents we hold in our huge knowledge base. Finding the right information is often exhausting (but not exhaustive) and time-consuming. To address this problem, we decided to use Amazon Kendra, a powerful new AWS offering. Kendra lets our scientists find the information they need by handling natural language queries quickly and accurately. With Kendra, we expect our engineers and researchers will find information much faster than they did before we used Amazon Kendra. Our scientists are enthusiastic about this new superpower and we expect them to be able to innovate faster, collaborate more effectively, and accelerate the ongoing stream of unique products for our customers.

Today's companies are inundated with vast amounts of documents and information on a daily basis, and finding the information you need quickly from past construction cases is a key challenge that directly affects employee productivity and work engagement. Amazon Kendra enables employees to instantly retrieve relevant information by simply asking questions in natural language. It also has an interface that allows searching from documents in a variety of formats, including PDF, WORD, EXCEL, and HTML, and can be easily integrated with existing data sources. As a result, Kendra enables employees at Taisei to find accurate information quickly and easily. Furthermore, by leveraging the Kendra Retriever API, we believe we can accelerate the development of generative AI applications such as retrieval augmentation generation (RAG) and support employee knowledge acquisition beyond the search system in the future.

The Wall Street Journal Talk 2020 tool seamlessly incorporates natural language search and Amazon Kendra makes it easy to keep data feeds updated. Talk2020 users can get the information they need to make important voting decisions by asking plain-language questions in order to find out what the presidential candidates have said on a wide range of issues and topics including: the economy, healthcare and COVID-19. We are glad to be able to provide this free service to anyone who wants to use it.

Amazon Kendra is a turnkey AI solution that, when configured correctly, is capable of spanning every single domain in the organization while being straightforward to implement.

Prior to our deployment of Kendra we attempted to create logical navigation paths to guide our customers to the information they needed; however, none produced the desired level of customer experience (CX) and could lead to frustration or worse, customers making less than optimal decisions about their health benefits. Amazon Kendra plugged in effortlessly to our existing portal platform and freed up staff members to focus on higher value activities to drive CX improvements. While we’re still early in our use of Kendra, we’ve already seen it support thousands of positive customer interactions and deliver higher quality answers in just the first few days.

We chose Amazon Kendra to build a secure and scalable agent assist solution. This helped call center agents and the customers they serve quickly uncover the information they need. Since implementing Contact Center Intelligence (CCI) and Amazon Kendra, early results show an average reduction in call times of about 9-15 seconds, which saves over 4k hours on over 2.2 million calls per calendar year.

To help cities better serve these residents, Citibot expanded its Amazon Lex chatbot to integrate with Amazon Kendra-- its ability to answer natural language questions, pulling in data from multiple sources, helps cities improve the scalability and effectiveness of engagement with constituents at a time when it is needed the most. During the COVID-19 outbreak, some cities have been reporting a 50% abandonment rate in their call centers, and some states have reported wait times of up to three hours with ~80% of volume being COVID-19 related. We expect Amazon Kendra to enable citizens to find the answers they seek quickly by engaging with the chatbot and reduce wait times by up to 90%. Post COVID-19, cities will continue to utilize the Amazon Kendra-powered chatbot to provide faster and easier access to more information about things such as public facility hours or road closures due to busy public events.

We needed a better way to connect our customers with the information they needed. First-time college students didn't know where to find program information on our site, which negatively impacted student enrollment rates, and returning students couldn’t locate updated office hours, resulting in a sub-optimal experience. Integrating this tool was straightforward; not only did it improve customer interactions by providing students with relevant answers, Amazon Kendra and Amazon Lex’s machine learning capabilities combined with the QnABot gave us a mechanism to better understand and meet our student’s needs, even during our busiest seasons. During peak we can receive over 2000 calls, which is too many for one agent to handle – however since launching the QnABot it’s supported over 34k conversations and saved 833 hours in staff time, while ensuring every customer received the same level of service and accuracy. For customers and students, this has been the most impactful technology that we've implemented. In the future we hope to expand our use of QnABot to provide personalized information to students as it relates to their academic schedules, advisement, and other relevant information related to their course of study.

Baker Tilly is excited about the impact Kendra will have on our client’s ability to make key decisions through data by providing access to repositories of knowledge in one quick, easy and accurate service.

To better equip our employees to deliver operational excellence for our clients, we undertook a project to modernize our internal knowledge base. We wanted to make it easy for staff to find the information they needed and boost employee engagement across the board. Initially we were challenged by the fact that a lot of our documents were located across different drives and content repositories making it difficult to classify and create a unified search index. With Amazon Kendra, instead of going down the road of classifying data, tagging documents, and managing taxonomies we were able to apply Amazon Kendra’s intelligent search capabilities so employees could ask natural language questions and get answers to HR or benefit-related topics quickly. This prevented employees from needing to know the name of the policy or where the document resides, enabling them to get relevant answers quickly and focus time on value-added activities. We’re excited by the potential of more intelligent search at JMT and have identified more areas where it can help our employees and customers going forward.

One of the most impactful things AI like Amazon Kendra can do right now is help scientists, academics, and technologists quickly find the right information in a sea of scientific literature and move important research faster. The Semantic Scholar team at Allen Institute for AI, along with our partners, is proud to provide CORD-19 and to support the AI resources the community is building to leverage this resource to tackle this crucial problem.

With 65 years of experience, including 35 years designing, building and operating LNG plants, we have millions of documents capturing our collective intelligence. Continuing our journey to becoming a cognitive enterprise, we are looking for greater precision in responses to our natural language questions, at a scale not previously possible. That’s why we have decided to use Amazon Kendra. Kendra uses natural language queries to retrieve specific answers our people need. We’re now able to precisely search our most valuable project engineering documents, and will soon scale this across our entire documented knowledge base. Kendra finds the answer to questions like ‘What is the length of the pipeline at Pluto?’ quickly and accurately. This step-change in cognitive capability will enable even better, faster decision making to improve our operations and the working lives of our people.

One of our core offerings is the Workgrid Chatbot, which provides employees the ability to get quick answers to frequent queries and automate tasks using a friendly, natural language interface. One key part of any enterprise chatbot is the ability to answer the myriad of questions that come from employees, which is why Workgrid offers a self-service Q&A builder that requires no programming language for content authors to train the chatbot to respond to employees’ questions. In addition to this curated content, we want to offer a way for the Workgrid Chatbot to easily extract knowledge from the vast quantities of documents (e.g., PDF documents) that exist across the enterprise. With Amazon Kendra, we’re excited about the possibility of our customers getting the answers they need quickly and efficiently. Amazon Kendra makes it possible to extract answers directly from unstructured data across multiple repositories and has the potential to fast track our delivery of accurate, better-than-before answers to our customers. We’re excited about exploring the combination of Amazon Kendra’s intelligent search with the conversational context and task automation that we provide to create a powerful employee experience.

At Sage we are always looking to partner with companies that help us solve customer challenges in new, smart ways. Organizations of all sizes face challenges with information discovery, which directly affects employee efficiency and experience – technologies like Amazon Kendra provide opportunities to address these challenges. We certainly see the benefit this might have for our customers across accounting and financials, payments and banking, people and payroll – who are looking to Sage to help their business. Our purpose is to transform the way people think and work so their organizations can thrive; using services like Amazon Kendra, we can support our customers to do just that.

At Haufe Group we continuously explore ways to improve the customer experience and seek to increase employee productivity through better technology. One key element to being efficient in today’s working environment is fast access to relevant data, including bringing together data that resides on distributed systems. Everybody has experienced challenges in finding the right information in the right place at the right time. Often, we are frustrated by the effort associated with finding the data we are searching for. Poor search experiences compound themselves when the search is performed on text based content, especially for document search. While there are already various approaches in place to optimize this search experience at Haufe Group, we are confident that Amazon Kendra will contribute significant additional optimization such as providing a single search experience across at least 7 key information repositories across the group and be key to achieving the speed and ease of access we desire. With its predefined connectors for different data repositories, and the option to create custom connectors, we expect Amazon Kendra to help with a broad range of use cases for improved customer experience and employee productivity.

Onix, an award-winning cloud consulting company with nearly 20 years of deep enterprise search experience, has helped hundreds of customers adapt to the ever-changing search landscape. Search capabilities have evolved over the years. Users now expect the same experience they get from the semantic and natural language search engines and conversational interfaces they use in their personal lives. Powered by machine learning and natural language understanding, Kendra improves employee productivity by up to 25%. With more accurate enterprise search, Kendra opens new opportunities for keyword-based on-premise and SaaS search users to migrate to the cloud and avoid contract lock-ins.

AWS has been essential in accelerating the development of Sherlock. We don’t have to worry as much about scaling, systems maintenance, and stability because AWS takes care of it for us. With Amazon Kendra and Amazon Lex, we’re able to build the best version of Sherlock and reduce our development time by months. On top of that, we’re also able to decrease the time for each literature search by 16%.