Resources

The Easy Way to Bring Enterprise Data to Gen AI

MongoDB Atlas and Amazon Bedrock make it incredibly easy and safe to simplify bringing enterprise data to generative AI using retrieval-augmented generation (RAG). RAG enables organizations to build hyper-personalized experiences uniquely tailored to business needs using enterprise data. MongoDB Atlas securely unifies real-time, operational, unstructured, and vectorized data, removing the friction of integrating the essential data components required to give large language models (LLMs) the context they need in a RAG workflow. At the same time, Amazon Bedrock offers a fully managed, end-to-end RAG workflow feature alongside a range of foundation models (FM) and tools for creating, training, and deploying generative AI solutions. Here, we explore how they work together to accelerate time to value for enterprises looking to build generative AI experiences that take advantage of their proprietary data.

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MongoDB and RegData: Securing Digital Transformation

The white paper addresses data protection challenges in financial services amid digital transformation. It introduces RegData Protection Suite (RPS), built on MongoDB, as a solution. RPS offers: Data protection through encryption, anonymization, and tokenization Compliance solutions for various financial regulations Support for multi and hybrid cloud deployments Management of outsourcing risks Zero-trust approach for AI applications Key benefits include: Simplifying deployment and modernization Streamlining compliance and auditing Enabling innovation while maintaining security RPS leverages MongoDB's flexibility and scalability to help financial institutions balance technological advancement with regulatory requirements, allowing them to modernize operations securely and efficiently.

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Optimizing your Internal Developer Platform with MongoDB Atlas

MongoDB’s mission is to meet developers where they’re at. That includes providing them with the best data platform for building modern applications. As implementing internal developer platforms (IDPs) becomes popular in developer organizations, choosing the right data solutions for IDPs can be a challenge for platform engineering teams. This white paper provides an overview of how MongoDB Atlas, MongoDB’s developer data platform, can make that choice easier and showcases how you can easily incorporate MongoDB into an IDP using the tools your developers are already familiar with.

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The State of AI Readiness 2024

AI can provide tangible benefits such as deeper insights, increased productivity, improved customer service, and operational efficiencies when it is deployed successfully. To achieve these benefits from AI, organizations need to understand the problems they want to solve and have a solid data foundation that supports high volumes of diverse data. Enterprises will need the right organization and skills to deploy AI into production and ensure that those models stay current. With the advent of generative AI, more organizations are feeling pressure to put an AI program to work in their company. However, if they don’t have the necessary foundations in place, it will be difficult for them to succeed. Readiness is not simply a matter of trying out AI solutions or building a predictive analytics model. AI readiness involves people, processes, and technologies. Read the new State of AI Readiness report today to learn about the current state of AI, how ready organizations are to implement it, and best practices for moving forward with AI.

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The Customer Analytic Record: Unlock CX Personalization and Profits in Financial Services

The Customer Analytic Record (CAR) serves as a centralized repository that aggregates various customer data across multiple touchpoints. This aids in understanding customer behavior and preferences, and it supports data-driven decision-making. With the CAR, banks and insurers can offer personalized customer experiences and efficient service, thereby fostering customer satisfaction and loyalty. Key Benefits of Implementing the CAR Solution: **Improving customer experience and satisfaction: **Deliver experiences that resonate with your customers by understanding their needs and preferences. **Reducing customer attrition: **Retain more customers by addressing their individual needs and concerns promptly and effectively. **Increasing personalization and tailoring: **Leverage comprehensive customer insights to provide personalized services and product recommendations. **Enhancing cross-selling and upselling: **Utilize data-driven insights to identify and act on cross-selling and upselling opportunities. **Advancing risk evaluation and underwriting: **Make informed decisions with enhanced risk assessment capabilities. Your journey to unlocking personalized customer experiences and increased profits is just a click away.

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Guarding the Gateway: Combatting Payment Fraud in the Digital Age

As payment systems advance, so do fraudsters’ exploits. Global card losses due to fraud are projected to total an astounding $397 billion during the next ten years. Our collaborative effort with MongoDB sheds light on the root causes of fraud, often found in financial institutions’ complex IT infrastructure, that allow fraudsters to exploit gaps and evade detection. This paper is a call to action for financial institutions. It provides solutions to this growing threat, especially for card-not-present transactions. These transactions are riskier and make fraud detection even trickier due to the lack of a physical card, chip, PIN, or signature verification. Download the paper now to learn: The most common types of fraud in payments How to identify and address typical gaps in fraud detection approaches Three critical components of a fraud detection approach A three-step method to prevent fraud and future-proof your organization Real-life examples Future-proof your business today with just one click!

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Real-World Results Blending JSON Document Management and High-Speed SQL

Market intelligence firm IDC recently examined the combination of MongoDB Atlas and SQL DBMS, Google BigQuery for operational and analytic use cases. In its report, Real-World Results Blending JSON Document Management and High-Speed SQL , the firm looked at the experience of two major users of this technology combination and detailed the business benefits they realized through the combination. According to the report, the users — a midsize parts supplier and a major investment advisory firm — achieved several major benefits as a result of the integration: 10X performance improvement Lower total cost of ownership Near 0 day-to-day operational maintenance Read the report now and find out why Google BigQuery and MongoDB Atlas were found to be highly complementary and how together they offered users complete operational and analytic support.

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The MongoDB AI Applications Program (MAAP): The proven path to AI Success

It’s an understatement to say that the AI landscape is ever-changing. To keep pace with the latest developments and customer expectations, access to trusted collaborators and a robust support system are critical for organizations who want to innovate with AI. This is why we created the MongoDB AI Applications Program (MAAP). A first-of-its-kind program, MAAP helps organizations rapidly build and put applications into production with advanced AI capabilities by providing them with reference architectures and an end-to-end technology stack that includes integrations with leading technology providers, professional services, and a unified support system to help customers quickly build and deploy AI applications. Download the datasheet to learn more about MAAP and how it can help accelerate your AI journey.

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Transforming Your Business Through Artificial Intelligence

Today, AI-powered intelligent applications are being used to transform business processes and thereby improve their performance, efficiency, effectiveness, and agility. Enterprises all over the world, in all industries, and of all sizes are implementing digital business transformation to varying degrees. Advances in cloud computing, real-time stream and event processing, low-latency data fabrics, and more – all accelerated by AI – are driving a continual feed of real-time data updates, contextual insights, optimized experiences, and fast results into all business processes. This TDWI Best Practices Report explores key trends, considerations, and opportunities associated with successful implementation of AI in enterprise digital business transformation initiatives, including: What challenges enterprises must address & key success factors in using AI for digital transformation The role of AI in transforming business processes and decision-making

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Atlas for the Edge

Atlas for the Edge provides a reliable solution that unifies the data across your distributed architecture. Learn how it enables critical, real-time use cases that drive operational efficiency, data-driven decision-making, bespoke customer experiences, and more. ###Ensure that digital actions reflect physical events Synchronize data across millions of sensors and devices with Atlas Device Sync and SDKs, ensuring uninterrupted access and real-time updates for critical edge applications. ###Prevent interruptions to local operations Deploy MongoDB anywhere with Atlas Edge Server to enhance availability, performance, and cost efficiency through localized data management. ###Leverage data insights to drive success with MongoDB Atlas MongoDB Atlas’s developer data platform provides a unified data layer with access to advanced features including real-time analytics, full-text search, and enterprise-grade security. Across industries companies are investing in edge solutions. Those building with MongoDB experience less barriers, resulting in quicker times to market, and accelerated returns on investment. To learn more about how companies are leveraging MongoDB Atlas for their connected infrastructure, download the Atlas for the Edge solution brief.

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Atlas Edge Server

Atlas Edge Server allows you to store and synchronize data to and from Atlas from your local or remote infrastructure. Learn how it can help ensure that mission-critical applications and devices function seamlessly, even in the most disparate and expansive environments. ###Optimize production operations Enable real-time equipment health monitoring and maintenance predictions for your smart factories that can be accessed by personnel locally, or across the globe. ###Enhance shopping experiences Prevent supply chain disruptions with instant inventory updates and provide bespoke in-store experiences for customers, across all of your retail locations. ###Improve fleet management Utilize real-time data to streamline supply chain logistics for optimized service scheduling, and prevent breakdowns by monitoring vehicle sensor telemetry. Download the Atlas Edge Server solution brief now.

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MongoDB’s FY24 Environmental, Social and Governance Report

MongoDB’s FY24 ESG Report (f/k/a Corporate Sustainability Report) provides an update on key initiatives in the areas of sustainability relevant to MongoDB: corporate governance and ethics, employee engagement, diversity and inclusion, cybersecurity, and environmental impact. We invite you to learn more about how we seek to positively impact our employees, the communities we operate in, and the environment. This report also includes disclosures on how MongoDB adheres to the SASB (Sustainable Accounting and Standards Board) reporting framework.

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