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.
Let us share the key learnings from a complex US-based software development project, working with distributed teams across six time zones.
In this post, our expert summarizes the different directions of cloud-native backend architectures, along with their recommended use cases.
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.
In this blog post we briefly summarize the key provisions of the EU AI Act 2024 about the risk categorization of various AI tools.
