Enterprise AI Readiness Assessments

Foundation layer with sovereign infrastructure, data governance, audit systems, compliance frameworks, and risk management. Required for all AI initiatives to ensure security, compliance, and scalability.

Hosted language models with usage tracking, ethical guidelines, fine-tuning infrastructure, and model evaluation. Required for employee productivity tools, content generation, analysis assistance, and conversational interfaces.

Enterprise system access with API standards, data connectors, RAG infrastructure, and role-based access controls. Required for AI to access real organizational data—document analysis, data synthesis, and enterprise search.

Autonomous agent deployment with containerization, lifecycle management, security isolation, validation systems, and threat detection. Required for automated workflows, process agents, and intelligent task routing.

Multi-agent coordination with workflow management, context sharing, cross-system monitoring, and human-in-the-loop approval. Required for complex multi-departmental processes and enterprise decision support.

Clients describe operational challenges in natural language. Our framework extracts structured requirements including user types, current processes, desired outcomes, constraints, volume, systems involved, and compliance criteria.

We assess your current state across all 5 layers, identifying what exists and what's missing. Layer-by-layer gap identification ensures no dependencies are overlooked in the implementation plan.

We identify required components per layer, ensuring no dependencies are missed. Systematic analysis prevents implementation failures by mapping all technical and business process components.

We calculate implementation costs and quantified benefits with ROI projections. Component-based estimation provides accurate budgets including development costs, operating costs, annual benefits, ROI, and NPV.

We generate phased deployment plans respecting technical dependencies. Roadmaps sequence work across layers ensuring foundational components are deployed before dependent capabilities.

White Glove Labs consultants conduct framework assessments using our AI-powered platform. Combines human judgment with AI efficiency for comprehensive analysis in 1-2 weeks (single use case) or 3-4 weeks (portfolio).

Deploy the assessment framework application within your infrastructure. Conduct unlimited ongoing assessments independently with complete data sovereignty and control. Build internal AI readiness expertise.

Reduce assessment time from 3 months to 2 days with our AI-powered framework and structured methodology.

Component-based estimation provides accurate cost projections, reducing budget overruns compared to traditional consultant estimates.

Systematic layer-by-layer analysis ensures no prerequisite components are missed in implementation planning.

Dependency-aware sequencing optimizes implementation phasing, reducing time to first deployment.