Automated Admissions Intake Queue

For

Admissions officers at language schools and vocational colleges

Solves

Administrative staff spend hours on repetitive inquiries and miss urgent tour requests due to heavy workloads

Delivers

Scheduled tour confirmations, approved reply drafts, exception case summaries

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For admissions officers at language schools and vocational colleges, turn email and web form submissions into scheduled tour confirmations and draft replies, and address the problem of missed leads and staff burnout.

1. Classify incoming message intent
2. Retrieve approved answers from knowledge base
3. Check live calendar availability
4. Draft tour confirmations
5. Summarise complex cases
6. Flag sensitive data for human review

What goes in, what comes out

The workflow

1. In
   Start with

   Email accounts, website form URLs, approved answer documents, calendar data, staff contact list

2. 1

   Receive message

3. 2

   Classify intent

4. 3

   Check calendar

5. 4

   Draft response

6. 5

   Route to review

7. 6

   Approve or edit

8. 7

   Send reply

9. 8

   Start with email and web form submissions and finish with scheduled tour confirmations and approved replies

10. Out
    Finish with

    Scheduled tour confirmations, approved reply drafts, exception case summaries

AI does the heavy lifting, people stay in charge

Use language models to interpret intent and draft text from a knowledge base. Use calendar APIs to check availability and propose slots. A staff member must review and approve all draft replies and confirm tour details before any message is sent

What your team sees

Key screens: Enquiry dashboard, calendar interface, approval queue. Use a central feed to show incoming messages with intent tags, a visual calendar for slot selection, and a review panel with draft text and approval buttons. Show the status of each message from received to approved. In this product, the first view is the enquiry dashboard, followed by the calendar interface and approval queue

Accounts and administration

User roles for staff and managers, message history, approval workflow states, audit trails of all interactions

Integrations and data access

Email inboxes, calendar applications, CRM systems

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   6 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will admissions officers at language schools and vocational colleges use it to solve "administrative staff spend hours on repetitive inquiries and miss urgent tour requests due to heavy workloads"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Compare response times and booking rates before and after implementation to prove the value of faster replies
4. Measure, then decide. Track average response time reduction and increase in scheduled tour bookings. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Connect a single email inbox, build a knowledge base from the top ten FAQs, and enable one-click approval for standard replies. Manual review is required for all tour scheduling and complex queries

After the MVP. Automate the scheduling of follow-up reminders, integrate with CRM systems, and handle multi-language responses

What the build depends on. Natural language processing models, calendar API access

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

$2,000 per month per client

Message to test

Stop losing enrolments to faster responses with an AI that drafts replies and schedules tours for you to approve

Where to find buyers

EdTech conferences, direct sales to school owners, LinkedIn

Lead magnet

A free audit of their current enquiry response time

The first 30 days

1. Week 1: Connect email and calendar.
2. Week 2: Build knowledge base and approve first drafts.
3. Week 3: Test tour scheduling logic.
4. Week 4: Full human review workflow launch

Paid pilot

Compare response times and booking rates before and after implementation to prove the value of faster replies

Success metrics

Average response time reduction, increase in scheduled tour bookings

Retention and expansion

Ongoing subscription based on the volume of enquiries processed

Why clients would pick it

The value comes from the curated knowledge base and the specific workflow integration, which becomes more accurate and useful as more conversations are processed

Alternatives and positioning

Staff use email clients and spreadsheets for scheduling. This differs by centralising intake, automating drafts, and enforcing a human review step

Main delivery costs

AI API costs, staff time for setup and maintenance

Strict permission to prevent sending unapproved messages, data masking for personal details, and limits on calendar availability to prevent double booking