Systems | Development | Analytics | API | Testing

Ep 9 - Bottlenecks to Breakthroughs: How Covetrus Solved Latency with Streaming

For enterprises managing sprawling systems and frequent M&A activity, data latency isn’t just inconvenient—it’s a blocker to business value. In this episode, Joe Pardi, Senior Director of Global Data Engineering at Covetrus, explains how his team replaced fragile data pipelines with a robust real-time data streaming architecture that enables instant decisions across the entire enterprise.

How QA teams can leverage AI assistants

AI has been booming and has become a transformative force in several industries, software testing and QA are no different. With the evolution of technology and complexity of applications, automation and big-volume data analysis require extra assistance, and that’s where AI might come in handy. In QA, AI could help improve the efficiency of test management tasks, reducing manual effort.

AI and the Future of Finance: Decoding Earnings Calls

In this episode, Dana Gardner, Principal Analyst at Interarbor Solutions is joined by Liam Hynes, Global Head of New Product Development at S&P Global Market Intelligence. They discuss how S&P Global Market Intelligence utilizes AI to analyze corporate earnings calls to guide and improve financial reporting. These insights help businesses enhance communication, refine executive performance, and predict market outcomes. The conversation also highlights the use of Snowflake Cortex AI platform and the importance of data-driven decision-making in the financial sector.

How to Master AI/LLM Traffic Management with Intelligent Gateways

As businesses increasingly harness the power of artificial intelligence (AI) and large language models (LLMs), a new challenge emerges: managing the deluge of AI requests flooding systems. This exponential growth in AI traffic creates what could be considered a gratifying predicament—high demand for your AI services—but also introduces complex challenges that must be addressed for sustainable operations.

How I Built an AI Agent to Automate Customer Support - No Complex Coding Required

What if you could build your own customer service agent that handles real-world support queries automatically, saving time for both customers and our team? Maryam Ahmad from our PRD team did just that using Astera’s low-code and drag-and-drop interface. With Astera AI Agent Builder, Maryam created an intelligent agent designed to handle key customer service tasks for an e-commerce platform: checking order status, cancelling orders, and providing information on refund and return policies, all through a seamless conversational interface.

Building AI Agents: 6 Tips for Success

AI has evolved rapidly—from basic algorithms that suggested content to generative models that create it. Now, we're entering the AI agent era. AI agents refer to sophisticated AI systems that use reasoning and iterative problem solving to achieve specific goals. Instead of waiting for instructions, they adapt and take initiative. Agentic AI has transformative potential for enterprises.