The answer is simple. Start with boring. Boring projects make money. Clients who address these three elements are more likely ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Companies hate to admit it, but the road to production-level AI deployment is littered with proof of concepts (PoCs) that go nowhere, or failed projects that never deliver on their goals. In certain ...

The foundation of an AI strategy is about vision, drivers and risks. It should focus on the essence of what an organization ...

We are living through one of those rare moments when an entire industry cycle is being reimagined. Like the internet revolution of the 1990s, artificial intelligence is fundamentally reshaping how ...

Google’s AI ecosystem includes over 30 tools categorized into seven groups, addressing needs like deep learning, content ...

Although 95% of AI projects fail, research shows that successful initiatives focus on infrastructure. Top hurdles include poor integration, lack of skill sets, and difficulty building in-house AI ...

AI in healthcare has reached a critical inflection point. Across the industry, organizations are investing heavily in artificial intelligence, believing it will revolutionize patient care, reduce ...

To make cloud or AI projects successful and complete them on time, you need a clear understanding of business goals and technology capabilities, and that understanding needs to be kept current and ...

AI projects have become the axis of capital flows and the main focus for investors. In 2025, AI startups raised $192.7 billion in global venture capital. At the same time, while some projects ...