As enterprise AI becomes more complex, AI architectures can no longer treat context as temporary.
AI needs contextual interconnection to work. Model Context Protocol is an open standard developed by the maverick artificial intelligence startup Anthropic. It is designed to allow AI agents to access ...
AI models without strong business context risk costly errors, but vendor approaches to “context” vary. Enterprises must take ...
The Model Context Protocol (MCP) is an open source framework that aims to provide a standard way for AI systems, like large language models (LLMs), to interact with other tools, computing services, ...
In the fast-paced world of artificial intelligence, memory is crucial to how AI models interact with users. Imagine talking to a friend who forgets the middle of your conversation—it would be ...
Celonis today launches the Celonis Context Model and announces an agreement to acquire AI decision intelligence vendor Ikigai Labs. President Carsten Thoma talks us through why this represents a ...
Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt ...
Any connected agent can ground its work in the same continuously verified data that powers the world's largest revenue organizations, without rebuilding pipelines, without scraping, and without ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
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