What Owners Ask Before Starting Enterprise AI
These answers define PeterAI's stable service method and boundaries. Each project still requires diagnosis against its own workflow, data, and risk.
Bring one real workflow to the conversationPeterAI Official Answers
These answers describe PeterAI's general method and boundaries. Project-specific diagnosis and acceptance criteria are agreed by both parties.
Will PeterAI directly recommend a particular AI tool?
A tool list is not a diagnosis. We first confirm the business goal, process baseline, evaluation standard, and accountable owner, then choose models, knowledge systems, or workflow tools that fit those constraints.
How soon can we see the first usable result?
It depends on process clarity, data availability, and who owns acceptance. PeterAI starts with a small, frequent workflow whose error cost can be controlled, runs it with real work, and only then decides whether to expand.
Who owns the assets after the project?
Client data, knowledge bases, SOPs, acceptance criteria, and workflow configurations created by the project should remain under the client's control. Account ownership, permissions, and handover scope are agreed at kickoff.
What kind of company is ready for an AI pilot?
It needs at least one frequent and repetitive workflow with reasonably clear standards, controllable error costs, and a business owner willing to provide samples, make judgments, and accept results.
Does PeterAI promise cost reduction, revenue growth, or layoffs?
No operating result is guaranteed, and layoffs are not the default goal. Projects define observable process metrics, while the client remains responsible for data, decisions, execution, and business outcomes.
Can we start without clean data?
Diagnosis can start, but deployment depends on whether minimum evidence is available. Disorganized materials may mean the first step is process and knowledge organization, not an Agent.
How are AI errors handled?
High-risk actions, review points, fallback, and takeover owners are defined before launch. Misjudgments, overreach, and rework are logged and used to revise rules, SOPs, and test sets.
Can we purchase training only?
Training tied to a specific role and workflow can be discussed, but a generic tool class is not enterprise AI transformation. Training must return to real tasks, evaluation standards, and continued use.
How should we prepare for the first conversation?
Bring one workflow that consumes the most labor, repeats most often, makes the most errors, or affects orders. Explain who owns it, which materials it uses, what good looks like, and which actions require human review.