As organizations embrace generative AI powered by Amazon Bedrock, they face the challenge of managing costs associated with the token-based pricing model. Amazon Bedrock offers a pay-as-you-go pricing structure that can potentially lead to unexpected and excessive bills if usage is not carefully monitored. Traditional methods of cost monitoring, suchContinue Reading
In Part 1 of our series, we introduced a proactive cost management solution for Amazon Bedrock, featuring a robust cost sentry mechanism designed to enforce real-time token usage limits. We explored the core architecture, token tracking strategies, and initial budget enforcement techniques that help organizations control their generative AI expenses.Continue Reading
The art of storyboarding stands as the cornerstone of modern content creation, weaving its essential role through filmmaking, animation, advertising, and UX design. Though traditionally, creators have relied on hand-drawn sequential illustrations to map their narratives, today’s AI foundation models (FMs) are transforming this landscape. FMs like Amazon Nova CanvasContinue Reading
Although careful prompt crafting can yield good results, achieving professional-grade visual consistency often requires adapting the underlying model itself. Building on the prompt engineering and character development approach covered in Part 1 of this two-part series, we now push the consistency level for specific characters by fine-tuning an Amazon NovaContinue Reading
The MERN (MongoDB, Express, React, Node.js) stack is a popular JavaScript web development framework. The combination of technologies is well-suited for building scalable, modern web applications, especially those requiring real-time updates and dynamic user interfaces. Amazon Q Developer is a generative AI-powered assistant that improves developer efficiency across the differentContinue Reading
Amazon SageMaker Unified Studio represents the evolution towards unifying the entire data, analytics, and artificial intelligence and machine learning (AI/ML) lifecycle within a single, governed environment. As organizations adopt SageMaker Unified Studio to unify their data, analytics, and AI workflows, they encounter new challenges around scaling, automation, isolation, multi-tenancy, andContinue Reading
In Part 1 of our series, we established the architectural foundation for an enterprise artificial intelligence and machine learning (AI/ML) configuration with Amazon SageMaker Unified Studio projects. We explored the multi-account structure, project organization, multi-tenancy approaches, and repository strategies needed to create a governed AI development environment. In this post,Continue Reading
In Part 1 of our series, we explored the foundational concepts of responsible AI in the payments industry. In this post, we discuss the practical implementation of responsible AI frameworks. The need for responsible AI The implementation of responsible AI is not passive, but a dynamic process of reimagining howContinue Reading
The payments industry stands at the forefront of digital transformation, with artificial intelligence (AI) rapidly becoming a cornerstone technology that powers a variety of solutions, from fraud detection to customer service. According to the following Number Analytics report, digital payment transactions are projected to exceed $15 trillion globally by 2027.Continue Reading
Today’s enterprises increasingly rely on AI-driven applications to enhance decision-making, streamline workflows, and deliver improved customer experiences. Achieving these outcomes demands secure, timely, and accurate access to authoritative data—especially when such data resides across diverse repositories and applications within strict enterprise security boundaries. Interoperable technologies powered by open standards likeContinue Reading
