Short answer: give DripTell AI one current, approved source for course facts, then send judgement calls to an admissions adviser. The AI can answer routine questions from workspace knowledge, capture programme interest and pass the conversation to a person with context. It should not invent seat availability, decide eligibility, interpret an unusual fee case or promise admission.
That boundary makes the DripTell AI workspace useful without turning automation into an admissions authority. The institution still owns the source and final decisions.
Build one approved answer packet
Start with the questions learners actually ask: course title, format, published fee, campus, start period, ordinary entry requirements and required documents. Put approved answers in one controlled packet instead of copying fragments from old brochures and chats.
Each fact needs an authoritative source, owner and review date. If the team cannot name the source, the AI should not present the information as settled. One clear packet is better than a large knowledge base whose versions disagree.
The DripTell education page describes AI-assisted replies using approved programme, fee and admissions knowledge. The capability is live, but it depends on material the institution maintains. DripTell does not certify a course description independently.
Separate published facts from admissions decisions
Published information can often be answered directly. A decision that depends on a learner's history, a live system or an exception needs a person or an authoritative connected source.
- 1ApproveName source and owner.
- 2AnswerUse current published facts.
- 3StopHold case decisions.
- 4Hand overCarry question and context.
| Learner question | Safe first route | Required evidence |
|---|---|---|
| What is the published course fee | AI may answer from the current approved packet | Dated fee source for that intake |
| Is the course online or on campus | AI may answer a published format | Current programme page or prospectus |
| Am I eligible with these qualifications | Admissions adviser | Learner details and institution policy |
| Is a place available today | Adviser or connected admissions system | Current intake availability |
| Can I receive a discount or transfer credit | Authorised person | Applicable policy and case review |
| Has my application been accepted | Admissions system or authorised person | Verified application record |
A published requirement says what applicants normally need; it does not determine whether one person qualifies. A published fee does not resolve sponsorship, instalments, exemptions or a changed intake.
Test one real learner journey
Before enabling broad coverage, test an easy fact, ambiguous phrase, outdated detail, eligibility question, unavailable intake and human request. Use test records, never applicant data.
Check the source retrieved, answer given, details captured and owner after handoff. The AI should say when it cannot confirm something, not make uncertainty sound confident.
Use DripTell automation to apply an approved routing rule, not create policy. Programme, language, campus or country fields can support assignment when configured. The institution still decides which field is authoritative and who owns exceptions.
Make the handoff carry useful context
A handoff should not make the learner start again. The adviser should see the question, programme, relevant details, earlier answer and why automation stopped. The shared inbox keeps conversation and owner together; the customer record can retain agreed lead context.
Keep context proportionate. Course interest and preferred campus may be useful; unrelated history is not. The current WhatsApp Business Messaging Policy is the official channel policy. It does not prove a DripTell feature or replace institutional privacy, consent and retention decisions.
Use clear handoff reasons such as eligibility judgement, unavailable information, fee exception, application status and human request. Check that the intended adviser could act without reconstructing the chat.
Keep the source current
Name one owner for every packet. Review it before each intake, after a fee or schedule change, and when advisers repeatedly correct an answer. Retire old documents, record each change date and retest affected questions.
Do not broaden the AI's authority because early tests look good. Add an answer type only when its source, owner, expiry rule and handoff boundary are clear. The benefit is consistent routine answers while decisions reach the right person.
Bring one current course packet and five difficult questions to a DripTell walkthrough. Ask to see the source, captured context and handoff outcome, not a generic demo.
Frequently Asked Questions
Can DripTell AI answer course fees
Yes, when the current fee is present in approved workspace knowledge. Route sponsorship, instalment, exemption and exception questions to an authorised person.
Can DripTell AI decide whether a learner is eligible
No. It may collect relevant details and explain published requirements, but eligibility is an institutional decision that needs the applicable policy and learner record.
Does DripTell know whether a course has open places
Not from a brochure alone. Live availability needs a current authoritative source or an admissions adviser. The AI should not guess from an old intake page.
What should an adviser receive at handoff
The original question, programme interest, relevant captured details, the answer already given, the reason for handoff and clear conversation ownership.
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