About CharliAI
Built to Control AI Exposure in Regulated Enterprises

The problem CharliAI was built to solve is simple: enterprise AI is moving faster than enterprise control. Sensitive data now flows through prompts, models, agents, workflows, APIs, vendors, and third-party platforms. In regulated environments, that creates breach, audit, compliance, and operational exposure.
CharliAI was created to close the control gap between enterprise AI ambition and production reality. The platform sits across enterprise systems to control how data is accessed, how policies are applied, how AI workflows execute, and how every action can be traced, audited, and defended.
Drawing on decades of experience in industrial automation, control systems, digital twins, and highly secure regulated environments, CharliAI was designed around a simple principle: automation only belongs in production when it can be controlled. That principle has shaped the platform from the beginning, bringing rigorous control, observability, and evidence capture to agentic AI workflows.
Built by Enterprise AI, Data, and Security Operators
CharliAI is built by a team with deep experience in enterprise AI, data infrastructure, automation, financial workflows, and regulated information environments. The company’s focus is not generic AI productivity. It is the control infrastructure required to make AI safe, traceable, auditable, and production-ready in sensitive enterprise settings.

Kevin Collins
Founder & CEO
His experience building AI and digital twin technologies for complex industrial environments shaped CharliAI’s core philosophy: enterprise AI must be controlled, observable, secure, and production-ready. Kevin’s work now focuses on helping regulated organizations control how AI accesses data, executes workflows, applies policy, and produces defensible outcomes

Joel Emery
Founder & CPO
That background is central to CharliAI’s engineering discipline. AI connected to real data, real systems, and real workflows cannot be treated as experimental. It must be controlled, observable, auditable, and production-ready from the outset. Joel’s experience building reliable systems for complex operating environments directly informs CharliAI’s approach to secure, controlled enterprise AI
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