Systems | Development | Analytics | API | Testing

Flink AI: Hands-On FEDERATED_SEARCH()-Search a Vector Database with Confluent Cloud for Apache Flink

With the advent of modern Large Language Models (LLMs), Retrieval Augmented Generation (RAG) has become a de-facto technology choice, employed to extract insights from a variety of data sources using natural language queries. RAG combined with LLMs presents many new possibilities for integrating Generative AI capabilities within existing business applications, specifically opening up many new use cases within the data streaming and analytics space.

The Rise of Agentic Workflows in Software Development

Imagine workflows so intelligent they can adapt to changing conditions, solve problems autonomously, and collaborate seamlessly across teams – all while freeing up your time for the tasks that truly matter. This isn’t science fiction; it’s the promise of agentic workflows. As the software development world races to keep up with evolving demands, agentic workflows represent a revolutionary leap, offering a smarter, faster, and more adaptive approach to managing complexity.

LLM Data Gateways: Bridging the Gap Between Raw Data and Enterprise-Ready AI

LLM Data Gateways are specialized tools that prepare and secure data for AI systems, ensuring better performance, compliance, and cost efficiency. They act as a bridge between raw data and large language models (LLMs), solving common challenges in AI like poor data quality and security risks.

How Leaders in Financial Services and Manufacturing Accelerate Business Outcomes with Data and AI

Some 70% of organizations are actively exploring or implementing large language model (LLM) use cases, but fewer than a third of generative AI experiments have made it into production. A common hurdle? The inability to access and leverage the data crucial for running AI applications effectively. Snowflake’s Accelerate 2025 virtual events dive into the challenges and myriad opportunities offered by AI.

Agentic AI Needs an API Backbone: Cultivating Discipline & Governance for Scalable Success

For organizations seeking to leverage agentic AI, the journey begins with a steadfast commitment to discipline and governance. This talk underscores that the true foundation of success in agentic AI adoption is a culture that values structured API capabilities and a rigorous approach to digital integration. By fostering disciplined practices and robust governance frameworks, businesses can establish the resilient API foundations necessary for automating complex processes and scaling AI-driven initiatives.

AI Data Management: Best Practices & Tools

Artificial Intelligence (AI) is transforming the way businesses manage, process, and analyze data. AI Data Management involves the use of machine learning (ML), automation, and intelligent data pipelines to enhance data storage, governance, integration, and security. As organizations deal with ever-growing datasets, AI-driven data management solutions ensure efficiency, scalability, and accuracy.

The Role of AI in Penetration Testing

Penetration testing is like a virtual security guard for your organization’s cybersecurity. It detects vulnerabilities before malicious attackers can exploit them. Traditionally, this process relied on skilled professionals manually probing systems for weak spots. However, with the rapid evolution of technology and the surge in cyber threats, the need for smarter, faster, and more adaptive testing methods has never been clearer.

EP 12: Welcome to the Fifth Industrial Revolution

On this episode of The AI Forecast, Mike Walsh talks us through what he calls the fifth and latest industrial revolution - and that’s AI. Mike is a futurist and expert in disruptive technologies. He’s a best-selling author, host of the Between Worlds podcast, and CEO of Tomorrow – a global consultancy helping organizations adapt to the challenges of the digital age.

Beyond the Hype: Gen AI Trends and Scaling Strategies for 2025 - MLOps Live #35 with Gartner

In this webinar, we explored the most pressing GenAI challenges and the newest strategies for implementing and scaling GenAI in 2025. Svetlana Sicualar and Yaron Haviv, AI industry leaders and veterans, referenced their work and vast experience with enterprise clients across regions and verticals. They explored key questions that every tech leader should be asking themselves.