Amazon Comprehend Customers and Partners

The commercial insurance industry operates using processes that are document intensive. Processing these documents requires manual entry, is costly, and prone to human error. We use AWS services to automate and streamline operational workflows, using Amazon Textract and Amazon Comprehend. Using machine learning we have been able to extract policy numbers, expiration dates, and many more insurance industry-specific attributes with reduced manual effort. We leverage Amazon Textract to extract data from documents at scale and Amazon Comprehend to classify and label unstructured content in documents and pull out insurance-specific entities.  “Our applications use Amazon Textract and Amazon Comprehend in conjunction with our own proprietary models to automate costly manual processes like document review and insurance application intake. We reduce customer effort, making it faster and easier to buy and sell commercial insurance. We are seeing great results using AWS machine learning.”

-Colin Toal, Chief Technical Officer, Chisel AI

"We strive to combine technology and business domain expertise to help our customers understand compliance risks in their supply chain. We needed a way to process compliance documents at scale. Our process is to read images and PDF documents with forms, tables, and free-form text and extract data of interest from within those documents. Amazon Textract's OCR technology enabled us to extract text from documents. Amazon Comprehend's context-aware NLP APIs extracted business-specific entities and their values from the text. We also incorporated humans in our workflow using Amazon Augmented AI (Amazon A2I), to have our teams review extracted data and provide feedback to the ML models and help improve them over time. Using this efficient mix of human and machine learning along with AppSync and Amplify provided us more accurate insights into our customers' supply chain risk and saved them hundreds of hours in manually reviewing documents. They can now get immediate feedback on whether their company is at compliance risk."

-Corey Peters, AI/ML Team Lead, Assent Compliance

“Understanding customer sentiment across various products or services are key to understanding the health of the business. Amazon Comprehend Targeted Sentiment allows our customers to not only understand sentiment for a conversation but also drill down to specific areas of product or business at scale."

-Praphul Kumar, Chief Product Officer, SuccessKPI

"We are very excited about the Amazon Comprehend Targeted Sentiment feature because it will enhance our existing open-ended survey response reporting in Gallup Access. We currently report overall sentiment related metrics and with this new feature, we will be able to provide more targeted sentiment within those survey responses. This will enhance the value proposition of our overall reporting and provide our users with more accurate and actionable data ." 

-Swapan Golla, Director of Analytics, Gallup

“Using Amazon Comprehend for PII redaction with our tokenization system not only helps us reach a larger set of our customers but also helps us overcome the shortcomings of rules-based PII detection which can result in false alarms or missed details. PII detection is critical for businesses and with the power of context-aware NLP models from Comprehend we can uphold the trust customers place in us with their information. Amazon is innovating in ways to help push our business forward by adding new features which are critical to our product suite."

-Chris Schrichte, CEO, TeraDact Solutions, Inc.

AWS and Amazon Business digital implementations into ExxonMobil's procurement organization is enhancing its global operations and preparing them for unexpected disruptions.  "We’ve worked with the Amazon ML Solutions Lab to develop a proof of concept aimed at maximizing contract utilization and further reduction of costs. One approach leverages Amazon SageMaker to improve identification of best-matched catalog items from free text entries in ExxonMobil’s eProcurement system, Smart by GEP. When catalog item descriptions are not readily available, we use Amazon Comprehend to create a bespoke classification model to map free text entries to supplier contract agreements." 

-Mariano Matzkin, Global MRO Procurement Manager, ExxonMobil

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"FINRA receives millions of documents with unstructured data to support investigative, examination, and compliance processes. Our investigators and examiners had to manually go through documents page by page or run very targeted searches to find what they needed. With Amazon Comprehend, we can quickly extract individuals and organization, match extracted entities to FINRA records, flag individual of interest, and detect similarities with other documents.”

-Dmytro Dolgopolov, Senior Director of Technology of FINRA

“Amazon Comprehend and Amazon Transcribe services allow VidMob to build high-quality machine learning text analysis into our Agile Creative Suite, enabling us to help brand clients understand content performance in ways never before possible. We are able to transcribe text from video content, and quickly analyze it using Comprehend, allowing us to surface actionable insights to both our creator community and our clients, giving them a strategic edge in the market.”

-Alex Collmer, Founder and Chief Executive Officer of VidMob

"At PubNub, we've found that chat and collaboration has emerged as a dominant use case across our global customer base...Combined with other AI offerings like Amazon Polly (text-to-speech), Amazon Comprehend (NLP), and Amazon Lex (chatbots), this will help make chat apps smarter and ultimately make it easier for our customers to grow their businesses internationally through high-performance and localized chat functionality.”

-David Hegarty, Director of Product Management, PubNub

"We use Amazon Comprehend to read an article and extract topics, which are automatically tagged using machine learning. Amazon Comprehend tags entities with the highest confidence and enables us to make more accurate earned media estimates to really determine ROI from social. We used to see earned media value as a very rough estimate, but not anymore."

-Bill Boulden, CTO of ClearView Social

"We're transforming the traditional ways of consumer research by introducing video and automating the analysis of this video to result in actionable, dynamic consumer personas. Integrating with AI and machine learning technologies from Amazon, such as Amazon Transcribe, Amazon comprehend, and Amazon Rekognition, we're able to take these videos, analyze them, and create profiles of each individual."

-Patrick Tedjamulia, Co-founder & CEO of VideoPeel

“Our Sparq platform connects your most important customer data from any source—including transaction, attitude, emotion, and intent data—to build dynamic customer profiles that give every team and business system a unified view of the customer. By integrating with Amazon Comprehend’s sentiment analysis capability, the platform now turns qualitative customer feedback into actionable insight, determining whether their feedback is positive, negative, or neutral at over 90% accuracy.”

-Nicholas Simon, Product Manager of Vision Critical

“Our business is focused on delivering the best marketing content possible for the brands that depend on us. Using Amazon Comprehend, we were able to significantly increase the quality and accuracy of our platform’s content analytics capabilities, which identifies the right content for the most impactful marketing campaigns. Amazon Comprehend allows us to focus on our core product and not worry about the heavy lifting associated with building our own machine learning models.”

-Ryo Chiba, CTO of TINT

"Mobile messaging connects brands and consumers in a way that is direct, personal and authentic. At Vibes, we process billions of mobile messages every month and there are deep insights latent in the vast number of messages we process. Amazon Comprehend enables us to quickly extract key phrases, detect sentiment, and model topics from unstructured message content—providing marketers with a deeper understanding of their performance and actionable insights to deliver rewarding customer experiences."

-Brian Garofola, CTO of Vibes

“We provide legal professionals with insightful research and analytics to help them make informed decisions. Therefore, we are always looking for better ways to discover insights from legal documents. Thanks to Amazon Comprehend's automatic machine learning (ML), we can now build accurate custom entity recognition models without getting into the complexities associated with ML. The entities that we care about the most, such as judge and attorney, can be identified quickly from over 200 million documents at above 92% accuracy.”

-Rick McFarland, Chief Data Officer of LexisNexis