Authoritative definitions for the terminology shaping enterprise AI automation — from neurosymbolic AI to English as Code.
An AI architecture combining neural networks for understanding with symbolic logic for deterministic execution, eliminating hallucinations in enterprise automation.
Read more →A patented approach where business rules in plain English serve as the actual executable program — not comments, not prompts, but real production logic.
Read more →AI systems that can autonomously plan, reason, and execute multi-step tasks to achieve business goals, going beyond simple chatbots or rule-based automation.
Read more →Artificial intelligence that creates new content — text, code, images — based on patterns learned from training data. The foundation for modern AI automation.
Read more →The next evolution beyond RPA: AI agents that understand, plan, and execute business processes autonomously with human-in-the-loop governance.
Read more →Software robots that automate repetitive tasks by mimicking human interactions with computer interfaces. A predecessor to AI-native automation.
Read more →The combination of AI, machine learning, and automation technologies to automate complex business processes that require cognitive capabilities.
Read more →A platform that enables non-technical users to create, deploy, and manage AI agents without writing code.
Read more →Using AI and automation to handle customer inquiries, route tickets, and resolve issues without manual agent intervention.
Read more →An enterprise strategy that combines multiple AI and automation technologies to automate as many business processes as possible across the organization.
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