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Kamper AI reads whatever a provider sends — rosters, fee sheets, timetable screenshots, PDFs, in English or Bahasa Indonesia — and turns it into a fully structured, billable, ready-to-publish onboarding. What used to take days of manual data entry now takes one review.
Happy Kamper onboards activity providers — sports academies, swim schools, enrichment centres — onto its booking platform. Onboarding Hiro Education Center in Jakarta surfaced the exact reason manual onboarding is slow:
• Every provider sends data in a different shape — a spreadsheet per class, a photo of a timetable, a PDF price list, notes in chat• It arrives in two languages — “Senin & Rabu”, “per bulan”, “Paket 8 Sesi” next to English columns• A fee list of 28 line items is useless until someone groups it into real billing plans by hand• Hundreds of students must each be matched to an activity, plan, location and weekly slot — row by row
"One large intake could swallow two full days of data entry before a single class went live."
Kamper AI runs the whole onboarding as a guided pipeline. Each step has its own specialised AI agent that reads the source material, extracts exactly what that step needs, validates it, and hands a clean draft to a human for a one-click approval.
Reads timetables and class lists — even a photo — into structured activities and cohorts: capacity, age range, format, weekly days and times.
Turns a flat 28-line fee list into real subscription plans — monthly cycle, session allowance, linked charges — one plan per recurring activity.
Matches every roster row to a parent, an activity and the right real plan — auto-assigning the single linked plan and reading 4× / 8× straight from the sheet.
Places each student onto their activity’s recurring cohort — days, times, location — even when the roster carries no schedule columns at all.
Connects each activity to the plans that can bill it, so students can be enrolled correctly — no invented or mismatched plans.
Nothing reaches live data without an operator approving the step. Publishing is additive and de-duplicated — it never overwrites students already onboarded.
"We didn’t replace the team. We gave them back nine out of every ten hours they used to spend on data entry."
— Founder, Happy Kamper
It onboards an activity provider end to end: the provider profile, its activities and cohorts, its charges and billing plans, and every student with the right plan and weekly schedule — from whatever files the provider already has (spreadsheets, PDFs, or timetable screenshots).
The extraction agent interprets English and Bahasa Indonesia natively — terms like “Senin & Rabu”, “per bulan”, and “Paket 8 Sesi” are understood in context and mapped to structured fields, with the source language preserved. Nothing is re-keyed by hand.
No. Every step is drafted by AI and approved by a human before anything is committed. Publishing is additive and de-duplicated — new students and enrollments are matched against existing records and never overwrite or remove anyone already onboarded.
A large provider intake that took roughly two days of manual data entry now runs in under an hour — extract, review, approve, publish — about a 90% reduction in hands-on time. The Hiro Education Center onboarding produced 800–900 enrollments in a single guided pass.
Bring your messiest provider file. We’ll run it through an AI onboarding pipeline live — and you’ll watch a two-day job become a one-hour review.
Book a walkthrough • See it on your data • Start in 1-2 weeks
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