Where AI earns its place. Where it does not.
Before you commit to a vendor or a build path, we map your operations and tell you which workflows are AI candidates and which are not. The output is a roadmap you can defend to your CFO and your auditor.
The problem
You are evaluating AI for your operations, or you already have it deployed and want to know whether the governance holds. Vendors show demos. Your team has opinions. Nobody has mapped the actual workflows to determine where AI earns its place and where engineering does the job better.
What we deliver
Workflow mapping. We map every process where AI is being considered. For each one, we test the same questions: is the task rules-based? Is the data structured? Is human judgment genuinely required, or is it actually a reading task? The mapping tells you which processes are automation candidates and which are not.
AI governance assessment. If you already have AI in production, we audit it against the framework that applies to your context: NIST AI RMF, ISO 42001, COSO adapted for AI, or the IIA AI Audit Framework. We look at governance structure, human-in-the-loop adequacy, data traceability, output explainability, and vendor concentration risk.
Gap analysis and roadmap. Where the architecture falls short of the standard. Which gaps carry the most risk. Which are cheapest to close. The output is a prioritized roadmap with effort bands and a suggested sequence.
Build, buy, or do-not. For each candidate, we recommend one of three paths: build it (custom, using the three-phase architecture); buy it (a vendor product fits and the governance is adequate); or do not automate it (the risk or cost exceeds the benefit).
What changes for you
You walk out with a map. You know which workflows are candidates, which are not, and why. You know where your current AI systems are strong and where the governance gaps sit. The roadmap sequences the work by priority, not by vendor enthusiasm.