Agentic AI using reinforcement learning is becoming a game changer in terms of technology for business use. Whereas typical AI methods rely on already curated big data, agentic AI can act on its own accord to make decisions and adapt to arrive at a shared outcome. With reinforcement learning, agentic AI can learn to arrive at desirable outcomes by following an optimal strategy through trial and error and applying learned rewards and penalties from a prior experience. The framework enables AI in domain-specific ways (specifically business) for critical needs ranging from reducing onboarding time for an individual merchant, modernizing the identity verification process, and enhancing identity graphs to identify suspicious or repeat offenders to improve security and efficiency.