Every recommendation ClouDonna produces follows the same eleven-step path, in the same order. No product is named until the reasoning that leads to it has already been established.
Discovery starts with what you're actually trying to achieve — not a product category. A goal like "reduce time to close the books" points to a different answer than "unify data across a merger."
Your industry, scale, and current technology landscape shape which approaches are realistic. The same goal can have a different right answer depending on what you're starting from.
The goal and context together imply a set of capabilities that have to exist — governance, scalability, integration reach — before any product enters the conversation.
Capabilities get made specific: which regulations apply, which systems must integrate, which teams need access, and on what timeline.
Budget, existing contracts, skills on your team, and risk appetite all narrow the field before a single vendor is named.
Only now does Discovery move to categories of answer — buy vs. build, centralized vs. federated — evaluated on fit to what's above, not on brand recognition.
Specific platforms are scored against every dimension above using the Donna Score model — a documented, evidence-based method, not a black box.
Who actually offers the technology, and how they're positioned to deliver it, gets evaluated separately from the technology itself.
How the solution actually gets delivered — in-house, staged rollout, phased migration — affects time to value as much as the technology choice does.
Where delivery capacity or specialist expertise is needed, qualified implementation partners are surfaced against the same evidence standard.
Everything above is synthesized into a single report: the recommendation, the evidence behind it, the trade-offs, and what to do next. This is what Donna AI produces today.
Donna AI runs this exact sequence through a guided, conversational assessment and produces a real Executive Decision Report.
Try Donna AI