Admissions, test prep, pricing, and delivery boundaries cannot be handled by vague AI filler.
The hard part is not typing one sentence
The hard part is aligning domain judgment, relationship history, and the right tone at the same time.
The customer asks one question, but you are also recalling what happened last time, what they care about most, what you should never overpromise, and how to say it without sounding templated.
The same answer should sound different for a parent, a warm lead, a long-term customer, or a student.
Digging through notes, checking facts, switching to AI, copying back, then rewriting tone is too much friction in a high-volume chat workflow.
What we are validating
Not an auto-reply bot. A draft-reply console beside the advisor.
Domain knowledge provides the answer, customer profile shapes the context, your own tone adjusts the phrasing, and the draft only reaches the input box. You keep the send decision.
Ask for missing facts first, then give a clear answer when the case is answerable.
Track stage, priorities, budget, red lines, and prior commitments.
Learn from replies you already approved so drafts sound closer to you.
Clarify, explain, reassure, move the deal forward, or set a boundary.
A typical moment
“With this score, can I still apply for computer science? Should I repeat a year?”
A strong reply does not jump to a conclusion. It first checks what is missing: province, ranking, subjects, budget, and preferred cities, then asks follow-up questions in a way the customer can accept.
“This is not something I would judge from score alone. Send me the province, score, ranking, and subject combination first, and I can help narrow down the realistic tiers.”
Stable boundaries
Start with trustworthy drafts. Stay away from high-risk automation.
The early version only validates whether real users want “domain judgment + personal tone + low-friction replies” enough to leave contact details.
Collect lightweight profile, limited context, professional advisory scenarios, draft replies, and human approval.
Scrape private WeChat history in the background, auto-send, simulate clicks, mass-send, or impersonate public figures.
Join the waitlist
If this happens every day in your workflow, tell us about your context.
We will prioritize real high-frequency users for interviews and pilot access, especially in training, admissions, consulting, private community sales, and knowledge businesses.
- You do not need to upload full WeChat chat history.
- We only collect contact details and usage context.
- Your feedback will influence which vertical we build first.