A 30-minute diagnosis to decide where enterprise AI should start
Most companies do not lack models. They lack a clear starting point. The diagnosis clarifies business scenarios, data readiness, team capability, and MVP scope before deciding whether to build training, Agents, knowledge bases, or automation systems.
Book diagnosisDIAGNOSIS OUTPUT
Who it is for
- Business owners and leaders deciding where AI should land first
- Teams that bought AI tools but have not formed stable workflows
- Companies with multiple AI ideas that need prioritization
- Teams preparing to build AI agents, RAG knowledge bases, or workflow automation
What we review
- Which workflows repeat often enough to be handled by AI
- Whether documents, spreadsheets, systems, APIs, and permissions are usable
- Who will use the output and who will approve it
- How to keep the first MVP narrow enough to avoid platform bloat
What you get
- AI opportunity list
- First 1-3 priority implementation scenarios
- Data and system readiness checklist
- 2-4 week MVP roadmap
- Next-step recommendation across training, Agent, knowledge base, or automation
This is not a course sales call or a blind development quote
We first judge whether AI is worth doing, what should be done first, and how far the first version should go. If the scenario is not suitable, we say it directly.
FAQ
What should we prepare?
A workflow you want to improve, current tool list, sample documents or spreadsheets, and the time or quality metric you want to improve.
Does diagnosis always lead to system development?
No. Some companies should start with training or templates, some with a knowledge base, and only some with an Agent MVP.
How long does an Agent MVP take?
When the scenario, materials, and permissions are clear, a first MVP can often be piloted in 2-4 weeks.
Do you serve clients outside Shenzhen?
Yes. JingMind is based in Shenzhen and serves knowledge-intensive teams nationwide.