Systems | Development | Analytics | API | Testing

In today’s fast-paced software development world, automation promises speed, efficiency, and accuracy. However, teams often face several obstacles as they move towards building a successful test automation practice. From choosing the right tools to maintaining scalability, the path can be filled with costly pitfalls if not navigated strategically. In this thought leader discussion, industry veterans Ravi and Ram share insights from decades of experience, covering real-world examples of test automation gone wrong and offering expert advice on how to overcome these challenges.

Discover how GEP, an AI-powered procurement company, utilized Confluent's data streaming platform to transform its generative AI capabilities. Integrating real-time data into their AI models enabled GEP to provide a contextual chat-based service. This chatbot allowed GEP customers to build their own tools simply by communicating in English with a chatbot.

Learn how GEP, an AI-powered supply chain and procurement company, harnesses real-time data streaming through Confluent Cloud to fuel its generative AI solutions. With seamless integration into Azure OpenAI services and GPT models, GEP’s generative AI chatbot delivers document summaries and risk management insights to its customers.

How do you ensure your software system is reliable from design to deployment? In this episode of Test Case Scenario, Jason Baum and Evelyn Coleman sit down with Saurabh Shanbhag, Software Engineer at DoorDash, to discuss the best approaches for preventing bugs and building reliable systems. Saurabh draws on his experience from Amazon, Uber, and DoorDash to explain how teams can focus on strong initial design, thorough testing, and smart monitoring to keep systems running smoothly.