Workflow-specific evidence
Capability is tested on the client’s selected work and agreed acceptance criteria.
About / Richmond, Virginia
Enterprise AI built with financial discipline and implementation depth.
RVAI Consulting LLC is a Richmond firm focused on private, client-controlled AI infrastructure for middle-market organizations.
01 / The company
A complete implementation service.
RVAI designs, deploys, integrates, validates, and supports enterprise AI systems on infrastructure controlled by the client.
The work spans model and hardware evaluation, inference infrastructure, company data access, enterprise integration, governed agents, production controls, user training, and managed operations. Technology is selected based on the required result—not attachment to a particular model or hardware vendor.
02 / Founder
Alexander T. Levy
Alexander’s background combines finance, enterprise performance management, analytics, data architecture, systems implementation, workflow automation, and self-hosted AI infrastructure.
- Former KPMG Finance and Enterprise Performance Management consultant
- Healthcare finance experience at HCA
- Finance and analytics work inside a private equity-backed company
- SQL Server data warehouse architecture
- Microsoft Fabric and Power BI implementation
- ERP data integration
- Financial planning and reporting
- Azure AI implementation
- Workflow automation
- Self-hosted model infrastructure
- Private AI platform architecture
- Passed the CFA Level I examination
Alexander earned a Bachelor of Science in Business Administration with a concentration in Finance from the University of Richmond.
03 / Operating principles
The standard is a system that works in production.
Private AI is not a model demo. It is an enterprise operating capability that must meet business, security, technical, financial, and governance requirements together.
Client control
Infrastructure, approved data flows, models, permissions, and governance are designed around the client environment.
Model independence
Models are evaluated as capabilities and requirements evolve, with licensing and regression review before change.
Financial discipline
Architecture and scope are connected to an explicit business case, cost model, and payback logic.
Production discipline
Security, acceptance testing, monitoring, backup, recovery, documentation, and ownership are part of implementation.
Practical transfer
Users and administrators are trained, and the operating knowledge is left with the organization.
Discuss the operating case
Bring the workflow, the constraints, and the economics.
RVAI will help determine whether private enterprise AI is technically feasible, financially justified, and appropriate for the organization’s security and operating requirements.
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