Systems | Development | Analytics | API | Testing

Dual MCP Support in Astera AI: What it is and Why it Matters

Enterprise automation didn’t start with AI agents, but they’ve had a much bigger impact than earlier automation methods, such as software scripts or bots. Modern AI agents can do a lot more than tackle repetitive tasks. They can reason through complicated workflows, choose the best course of action, and access tools to execute said action. But to do all this, AI agents require interoperability. They need to be able to connect to numerous tools, databases, services, and APIs.

Perfecto AI: Financial Trading App Stock Simulator

This video demonstrates Perfecto AI in action, showcasing its advanced test automation capabilities within a financial trading app stock simulator. See how Perfecto AI, powered by Perforce Intelligence, eliminates the need for brittle scripts and manual frameworks — instead delivering AI-driven actions and natural language prompts that automate testing processes from setup to validation. Observe how it verifies critical components like graphs, colors, and trends, delivering consistent and reliable results even as user interfaces evolve.

Beyond the Buzz: Predicting the Next Five Years of Data AI Gateways

Data AI Gateways are reshaping how businesses manage APIs by automating key processes like creation, security, and scaling. These platforms simplify API operations, reduce costs, and improve efficiency, making them essential for enterprises navigating AI adoption. Here's what you need to know: What They Do: Automatically generate APIs, enforce security (e.g., RBAC), and integrate multiple databases. Why They Matter: Tackle challenges like siloed systems, scaling, and AI governance.

How to Securely Use LLMs with Your Data | DreamFactory AI Gateway

How can I securely connect an LLM to my database?! Get ready to unlock the full power of AI with DreamFactory’s upcoming AI Data Gateway! This new capability empowers teams to securely expose data to AI clients, tools, and agents—without sacrificing enterprise-grade control. RBAC-protected dataset access Fine-grained, zero-trust data exposure Seamless integration with OpenAI, Claude, LangChain & more Machine learning-ready APIs with instant insight delivery.

TDC S6E12 16x9 v02

Step inside the world of data innovation as Cindi Howson talks with Josh Cunningham, Group Head of Data and AI Culture at @lloydsbankonline. They'll explore how this distinguished institution is driving forward with cutting-edge AI. Discover how Lloyds is rapidly expanding its data and AI graduate scheme and pursuing an ambitious quest to become the "most data literate bank". Hear how innovative initiatives like the "Data and AI Summer School" and a physical "Data Escape Room" are used to teach "learning by stealth", propelling their business forward on data and AI.

Build Your Own Internal RAG Agent with Kong AI Gateway

RAG (Retrieval-Augmented Generation) is not a new concept in AI, and unsurprisingly, when talking to companies, everyone seems to have their own interpretation of how to implement it. So, let’s start with a refresher. RAG (short for Retrieval-Augmented Generation) is a technique that injects relevant data from an external knowledge source directly into a prompt before sending it to a Large Language Model (LLM). “But wait, my model is already fine-tuned on my domain-specific data.