AI Readiness Assessments
AI initiatives fail when the foundational data and infrastructure are not ready. We conduct deep-dive technical audits of your current architecture, data maturity, and workforce capabilities to give you a clear, objective score of your AI readiness and a roadmap to fix the gaps.
Core Features
Data Maturity Scoring
Evaluating the quality, accessibility, and cleanliness of your data silos to see if they can actually support machine learning models.
Infrastructure Auditing
Reviewing your current cloud (AWS/GCP/Azure) or on-premise setup to calculate the compute scaling and security gaps.
Security & Compliance Check
Identifying immediate red flags where your current data structure would violate privacy laws (GDPR/HIPAA) if exposed to an LLM.
Workforce Capability Review
Assessing your internal IT and engineering teams to determine if they need upskilling or external hiring to support AI.
Our Process
Stakeholder Alignment
Week 1Interviewing key executives and department heads to understand their business goals and where they believe AI can help.
Technical Deep-Dive
Week 2-3Our engineers get read-only access to your architecture, databases, and codebases to map the actual reality of your tech stack.
Gap Analysis
Week 4Comparing your current state against the required state for your desired AI use cases (e.g., 'You want RAG, but your PDFs are unsearchable images').
Roadmap Creation
Week 5Developing a step-by-step technical roadmap detailing exactly what data engineering and infrastructure work must be done before AI can begin.
Executive Presentation
Week 6Delivering the comprehensive report to the C-Suite, translating complex technical blockers into clear business decisions.
Technologies We Use
FAQ
Why can't we just buy ChatGPT Enterprise?
Who needs to be involved in this assessment?
Do you fix the problems you find?
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