Skan AI has introduced the Agentic Business Context Foundation (ABCF), a new intelligence framework designed to help enterprise AI agents operate more effectively in complex business environments by capturing operational context often overlooked by traditional enterprise systems. The framework focuses on integrating human reasoning, informal workarounds, exceptions, and decision-making patterns into AI-driven workflows, enabling agents to better handle real-world enterprise scenarios beyond standard documentation and event logs. According to Skan AI, AI agents typically perform well in structured situations but struggle with edge cases such as regulatory variations, quarter-end processes, and exception handling, where much of the critical business activity occurs.
Also Read: Expert.ai and Fincons Expand Partnership to Advance Neuro-Symbolic AI Adoption
Built on years of observational analysis across Fortune 500 organizations, ABCF combines behavioral work intelligence with Skan’s previously launched Agentic Ontology of Work and continuously improves through execution feedback loops. “The enterprise AI community has converged on the right architectural direction with context graphs and business context layers. What is consistently underestimated is where the operational context actually comes from,” said Manish Garg, Co-founder and CTO of Skan AI. The company positions ABCF as a foundational operational intelligence layer that strengthens the reliability and autonomy of enterprise AI agent architectures.