Reliable agents need more than generic intelligence. They need datasets of real work: the decisions, exceptions, context, handoffs, and domain-specific judgment behind how work actually gets done. That data is difficult to access, difficult to structure, and rarely captured in clean form. Specific is an AI lab solving that problem, turning real workflows into the foundation for dependable, domain-grounded agents.