Financial services
Intake and document chasing inside your compliance rules, so licensed staff spend their day on files that are ready.
AI service
Hands-on AI training for teams, using the company's own work
This is hands-on training for teams that have AI tools such as ChatGPT, Claude or Gemini but no shared way of using them. The sessions run on the company's own documents and tasks, so what people practise is the work they go back to afterwards. You also get a written AI usage policy that says which data may go into which tool, and a track for managers on choosing use cases and measuring them.
Deliverables
What you get
01
Exercises built from the team's own material
Practice tasks made from the team's documents, emails, spreadsheets and recurring work, with anything confidential removed or replaced before the session.
02
Prompt patterns that hold up
A short set of patterns staff can reuse: giving the model context and an example, asking for a fixed format, having it check its answer against the source, and recognising when a task is quicker done by hand.
03
Written AI usage policy
A plain-language policy naming the tools staff may use, what data may go into each one, what a person must check before it leaves the building, and who to ask when unsure. Client records and personal information get their own rules.
04
Small automations
Participants build small automations for their own work, such as summarising a weekly report or drafting replies from a template, and keep using them after the training.
05
Manager track
Separate sessions for managers on picking use cases worth the effort and measuring them after rollout, so decisions rest on figures from the team itself.
How it runs
The steps, in order
- 1
Learn how people work now
Short conversations with team members and a look at the tools already in use show which tasks eat time and which data is sensitive. That sets the exercises and the policy.
- 2
Draft the policy
We draft the usage policy with whoever owns IT and compliance, so the training teaches rules the company has already agreed.
- 3
Run the training
Delivered as a workshop or as a multi-week program. People work on their own tasks, in the tools they are allowed to use, for most of the time.
- 4
Follow up
Afterwards we review what people built and where they got stuck, then update the prompt patterns and the policy.
What we build with
- ChatGPT
- Claude
- Gemini
- OpenAI
- Python
Industries
Where it fits best
Education
Trial-class questions answered in English and Chinese on WeChat and your website, with the trial booked into your timetable.
Commercial real estate
Portal inquiries answered from your listing sheets within minutes, with the tour booked on the broker's calendar.
Dental and medical clinics
Booking, reminders and recall through your practice software, with patient data kept in the systems you have approved.
Building materials
Spec and stock questions answered from your own data, and contractor lists turned into draft quotes your sales desk approves.
FAQ
AI training for teams: common questions
Our staff already use ChatGPT. What does training add?
Self-taught use tends to settle into a few habits, and it rarely comes with rules about what may be pasted in. Training works on your own tasks and puts a written policy behind the habits it teaches. People end up using AI on more of their work, within limits the company has agreed.
What data can our staff put into AI tools?
That depends on each tool's plan and data terms and on what you owe your clients, and settling it is the job of the usage policy. A typical policy separates public material, internal documents and client or personal information, and names the tools approved for each. We draft it with you, and you approve it.
Is it a workshop or a longer program?
Either. A workshop suits a team that needs the basics and a policy in place quickly. A multi-week program suits a team that wants to build automations and bring questions back between sessions, and we recommend one after talking to the team.
Do participants need technical skills?
No. The main track works in the chat tools people already have. The automation exercises are chosen to match the group, and anyone who wants to go further gets material to do so.
How will we know the training worked?
The manager track sets this up before the sessions: pick a few tasks, record how long they take and how often they need rework, and check the same measures afterwards. That gives you figures from your own team instead of general claims.
What does AI training cost?
It depends on the format and the number of groups, and on how much preparation the exercises and the policy need. Sessions built on your own documents take more preparation than generic ones, and that preparation is where the value is. We quote once we know the team and the format.
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Tell us about the workflow that costs you the most time
A first call is about the business you run, not a pitch. We will tell you what an agent could handle, what it should not, and what it would take to build.