Making inherently probabilistic and isolated large language models (LLMs) work in a context-aware, deterministic way to take real-world decisions and actions has proven to be a hard problem. As we ...

What if the next generation of AI systems could not only understand context but also act on it in real time? Imagine a world where large language models (LLMs) seamlessly interact with external tools, ...

The Model Context Protocol (MCP) is redefining how artificial intelligence (AI) systems interact with external tools and services. By addressing the inherent limitations of large language models (LLMs ...

Imagine binge-watching a TV series, but you can only remember one episode at a time. When you move on to the next episode, you instantly forget everything you just watched. Now, imagine you can ...

As enterprises adopt AI, many are discovering that context, not model sophistication, determines whether systems can be ...

As organizations push AI systems into production, IT teams are asking how to make models more dependable, secure and useful in real-world workflows. One approach gaining traction is the Model Context ...

Contextual AI Inc., an artificial intelligence development startup founded earlier this year, exited stealth mode today with $20 million in seed funding. Palo Alto, California-based Contextual AI ...

AI systems fail because of a context gap—when decisions rely on incomplete, inconsistent and outdated data across systems.