Celadon
ServicesCeladon helps leadership teams identify high-value AI opportunities, assess current workflows and constraints, and determine where AI can create measurable business value — before a build is committed.
Get an AI Audit →Most AI value is lost before a line of code is written, in choosing the wrong things to build. That is what an audit prevents.
Most companies do not lack AI ideas. They lack a clear way to decide which ideas are worth pursuing.
The result is usually one of three problems: scattered experiments, vendor-led demos, or internal enthusiasm that never becomes operational. An AI Audit creates a structured way to evaluate where AI fits, where it does not, and what should happen first.
Celadon uses the audit to separate signal from noise. The work is focused, bounded, and designed to produce an executive-ready view of the opportunity, risks, architecture considerations, and next best phase.
Where AI may create value across revenue, cost, risk, productivity, customer experience, and operational efficiency.
How work actually happens today: who does the work, where handoffs occur, what systems are used, and where repeated decisions or manual effort cluster.
The documents, systems, structures, and knowledge sources that would need to support a useful AI system.
Whether the proposed use cases can be supported with available data, workflows, integrations, vendors, and operational constraints.
Where AI may introduce legal, compliance, brand, security, privacy, or operational risk.
Whether teams will actually use the proposed solution, and what enablement, training, workflow design, and leadership support it would require.
A clear, interest-aligned recommendation on which AI platform and models fit each use case — Claude, ChatGPT, Microsoft Copilot, Gemini and others — weighed on data retention (ZDR), US hosting, security and admin controls, agent capabilities, and total cost. Not a vendor pitch: a recommendation made in your interest.
How enterprises choose between Claude, ChatGPT & Copilot →A structured view of where AI can create value across the business.
A ranked list of opportunities by business value, feasibility, risk, operational fit, and time-to-impact.
A summary of workflows, systems, documents, bottlenecks, and constraints that shape the AI opportunity.
Whether each priority use case should be handled with a vendor, a custom build, an internal workflow, or no AI at all.
Early architectural decisions that determine whether the work can move into production.
What needs to be solved before implementation: data quality, access controls, workflow ownership, governance, and adoption.
Align on the business area, workstreams, constraints, and questions the audit needs to answer.
Review workflows, tools, documents, systems, team behavior, and existing AI activity.
Where AI can reduce manual work, improve decisions, accelerate research, support customers, or improve internal execution.
Each opportunity is evaluated against value, feasibility, risk, data readiness, and adoption likelihood.
A clear recommendation on what to build, what to avoid, and what to scope next.
An AI Audit is not a generic brainstorming session. It is not a vendor demo. It is not a theoretical AI strategy deck. It is not a mandate to build something.
The purpose is to determine what is worth building, what should be avoided, and what deserves more detailed strategy or implementation work.
A focused AI Audit gives leadership a clear view of where AI can create value, what constraints need to be solved, and what should happen next.
A focused conversation to understand your goals, constraints, systems, and highest-value AI opportunities.