The biggest obstacle to modernizing legacy systems is that we don’t completely understand how the system works, and there is no comprehensive documentation. This is where AI-Assisted System Discovery can help.
AI and Databricks in practice: our workshop focused on real-world examples and solutions, with detailed presentations on AI-assisted testing, DWH-Databricks migration, and AI-assisted SDLC.
AI in software development? Today, that’s no longer a question.
The question is “how.” Instead of simple code generation, it’s worth thinking about the entire development lifecycle.
AI can improve efficiency in many areas of business operations, including software development and testing, the standardization and transformation of various unstructured data, and customer service.
In this post, we share the challenges and key learnings of an AI chatbot development project.
There are cases where using AI tools may even hinder software development. Read the post to find out more.
Can AI support the work of software testers? What could be the role of AI agents? Find out in our blog post.
In the second part of our blog post we will specifically discuss how an LLM hosted in the Microsoft Azure environment can be a good solution to ensure data privacy.
AI behind the scenes: Our workshop focused on real-life experiences and solutions, discussing AI-supported testing, the relationship between AI and compliance, and a real-life case study.
In this blog post we provide a general AI Data Privacy Guide and best practices for companies using LLMs.
