Category: Amazon Machine Learning
Large language models like Amazon Bedrock can generate MongoDB queries from natural language questions, transforming how users access NoSQL databases. By leveraging AI and language models, this solution allows business users to query MongoDB data through conversational English instead of code. It connects to MongoDB with PyMongo, generates queries with LangChain and Bedrock, retrieves and formats results into natural language answers.
MLOps applies DevOps principles to machine learning, enabling organizations to efficiently develop, deploy, and manage models at scale. Eviden’s 10-step MLOps assessment examines existing models, establishes governance, creates self-service access, scales data analysis, registers models, enables feature re-use, provides data access, tests models at scale, deploys models, and enables API access. This end-to-end approach streamlines model creation and deployment while ensuring governance and consistency.
Healthcare organizations have vast amounts of valuable but siloed data. A new solution from AWS Partners Redox, Cloudwick, and ClearDATA helps healthcare customers use AWS HealthLake to extract value from their data. Redox integrates and translates data into AWS, while ClearDATA provides 24/7 security and compliance, and Cloudwick Amorphic enables teams to quickly build analytics and workflows to improve care.
Rapyder’s Call Agent Analyzer uses generative AI on AWS to revolutionize call center operations. It efficiently processes multilingual audio, summarizes calls, analyzes script adherence, and structures insights into actionable data. This solution helps businesses enhance customer satisfaction through data-driven call agent performance evaluation and training. As an AWS Partner, Rapyder provides cutting-edge cloud solutions that are reshaping industries like customer service.
Infosys is leveraging AWS generative AI capabilities like Amazon Bedrock and AWS Trainium to enhance its enterprise solutions. For example, Infosys Personalized Smart Video uses Amazon Bedrock to create rich, dynamic video content, while Infosys Cortex applies generative AI to analyze call transcripts and improve customer engagement. Overall, Infosys is rapidly adopting AWS’ flexible and scalable generative AI services to boost automation, productivity and user experience across its portfolio.
AWS Partner Generative AI Playbook, Partner Marketing Kits, Customer Journey Insights, and Market Data
AWS launched a Generative AI Center of Excellence to help partners keep pace with rapid advancements in generative AI. The CoE provides exclusive resources like playbooks, trainings, and marketing assets to educate partners on building solutions using AWS generative AI services. We’ll continue adding generative AI resources to accelerate strategies that enable partners to help customers adopt generative AI securely, responsibly, and cost-effectively.
Organizations face challenges managing and sharing knowledge. Traditionally, employees waste time searching documents or asking experts for guidance. AI assistants address this by quickly providing relevant, personalized responses. As Cognizant’s HR assistant use case shows, generative AI solutions enable self-service access to tailored knowledge that can reshape workplace efficiency by streamlining processes, reducing response times, and empowering employees.
In a recent webinar, Slalom and AWS showcased the incredible potential of chat-based enterprise search powered by AWS generative AI services like Amazon Bedrock. We’re excited to share key takeaways and a more in-depth exploration of the transformative landscape that chat-based search creates. Learn how technologies like Amazon Bedrock empower businesses to build intelligent chat-based interfaces that allow employees to interact with company data conversationally.
Leveraging Neo4j and Amazon Bedrock for an Explainable, Secure, and Connected Generative AI Solution
Neo4j is a graph data platform that, together with Amazon Bedrock, offers a compelling value add to any enterprise. Learn about the knowledge retrieval and extraction processes and review a couple of retrieval augmented generation (RAG) application architectures. Using Amazon Bedrock and Neo4j, you can simplify the knowledge extraction process which can be more complex and manual using traditional NLP libraries.
The ability to accurately share and analyze patient information between different healthcare providers and systems is critical to the transition to patient-centric care. Learn how AWS and Accenture collaborated to build a population-scale research cohort analytics solution called Accenture Health Analytics (AHA) which contains 54 million longitudinal patient records using a range of AWS services. It helps healthcare organizations improve patient outcomes and reduce delivery costs.