🤖 Business Onboarding Cookbook: Robotics, AI & STEM Learning Labs

Category: Robotics, AI & STEM Learning Labs
Primary Domain: 07_Education_Tutors_Coaching
Platform: 360 SERVICE HUB

1. Overview & Business Profile Context

This cookbook provides realistic, comprehensive, and verified test data for onboarding an experiential STEM innovation lab and children's robotics academy. It exercises:

• Shared Hardware Workstation Lab (SPACE) with Multi-Seat Pooled Capacity ($N=10$): Modeling hands-on electronics and coding laboratories where up to 10 student stations operate in a batch cohort.
• Dedicated Mentorship vs. Batch Workshop (PERSON + SPACE + EQUIPMENT): Demonstrating group weekend robotics classes versus 1-on-1 private mentoring for international robotics Olympiad competitions.
• Minutes Duration Engine with 90-Minute Lab Modules: 90-minute immersive coding and prototyping blocks with a mandatory 15-minute component re-sorting and test buffer.
• Physical Component Safety & Micro-Inventory Buffers: Dedicated turnaround buffers for soldering tip cooling, breadboard component sorting, and robotic arm servo resets.
• Weekend-Heavy Academic Calendar: Optimized for after-school Wednesday–Friday evening batches and full-day Saturday–Sunday bootcamps.

2. Step-by-Step Onboarding Data

Step 1 of 5: Business Information

Step 2 of 5: Add Resource (Polymorphic Flow)

Add the following 3 realistic resources covering 2 hardware innovation labs and 1 senior robotics mentor:

[ What does your customer book? ]
 ├── [○] 1. Room / Space         ──► Lab 1: Arduino & Microcontroller Maker Space (Capacity: 10)
 ├── [○] 2. Room / Space         ──► Lab 2: LEGO Spike Prime & AI Robotics Studio (Capacity: 10)
 └── [●] 3. Team Member / Staff  ──► Dr. Siddharth Rao (Lead Robotics Mentor & PhD Mechatronics)

Resource 1: Lab 1: Arduino & Microcontroller Maker Space (Room / Space — Capacity N=10)

Resource 2: Lab 2: LEGO Spike Prime & AI Robotics Studio (Room / Space — Capacity N=10)

Resource 3: Lead Robotics Mentor (Team Member / Staff)

Step 3 of 5: Services & Offerings

Configure the following 4 realistic STEM offerings covering group lab bootcamps, AI vision coding, and 1:1 Olympiad mentoring:

[ Services & Offerings Portfolio ]
 ├── 1. Weekend Robotics & Drone Building Bootcamp (90 mins | ₹1,200 | Multi-Seat N=10 | Lab 1 + Mentor)
 ├── 2. Python AI & Computer Vision for Kids (90 mins | ₹1,000 | Multi-Seat N=10 | Lab 1)
 ├── 3. LEGO Spike Prime Robotics Discovery (90 mins | ₹900 | Multi-Seat N=10 | Lab 2)
 └── 4. 1-on-1 WRO / Olympiad Elite Project Mentorship (60 mins | ₹2,500 | 1:1 Dedicated Mentor + Lab 2)

Offering 1: Weekend Robotics & Drone Building Bootcamp (Minutes — Multi-Seat N=10)

Offering 2: Python AI & Computer Vision for Kids (Minutes — Multi-Seat N=10)

Offering 3: LEGO Spike Prime Robotics Discovery (Minutes — Multi-Seat N=10)

Offering 4: 1-on-1 WRO / Olympiad Elite Project Mentorship (Minutes — 1:1 Compound)

Step 4 of 5: Availability & Working Hours

Configure operational calendar optimized for Wednesday–Sunday afternoon/evening sessions:

Weekly Schedule Grid

Staff-Specific Availability Overlay

Advanced Operating Settings

Step 5 of 5: Booking Rules, Fulfillment & Policies

3. Five Deterministic End-to-End QA Test Scenarios

Scenario 1: Multi-Seat Workshop Seat Decrement & Satiation ($N=10$)

• Action: On Saturday at 10:00 AM – 11:30 AM in Weekend Robotics & Drone Building Bootcamp:
  • Parent A registers 2 children (2 seats).
  • Parent B registers 3 children (3 seats).
  • Parent C registers 5 children (5 seats).
• Expected Result:
  • Seat count progresses: $10 \to 8 \to 5 \to 0$.
  • At 0 seats, the 10:00 AM Saturday slot is marked "SOLD OUT".
  • Parent D attempting to book 1 additional seat is presented with the afternoon 02:00 PM slot.

Scenario 2: Compound Lock of Mentor Across Services

• Action: On Saturday at 03:00 PM – 04:30 PM, Dr. Siddharth Rao is assigned to teach Weekend Robotics & Drone Building Bootcamp in Lab 1. Concurrently, another parent attempts to book 1-on-1 WRO / Olympiad Elite Project Mentorship with Dr. Rao at 03:30 PM.
• Expected Result:
  • Because Dr. Rao is already committed to the group bootcamp from 03:00 PM to 04:45 PM (including 15m buffer), his availability calendar is blocked.
  • The 1-on-1 mentorship service displays 03:30 PM as unavailable and suggests 05:00 PM instead.

Scenario 3: Closed Days & Inventory Audit Validation

• Action: Customer queries availability for any robotics service on Monday or Tuesday.
• Expected Result:
  • The booking calendar displays Monday and Tuesday as grayed-out "Closed" dates.
  • No selectable time slots are generated.

Scenario 4: Station Hardware Reset Buffer

• Action: A Python AI session ends in Lab 1 at 05:30 PM. A parent attempts to book a workstation slot at 05:35 PM.
• Expected Result:
  • The 15-minute buffer reserves the lab from 05:30 PM to 05:45 PM for system cleanup and code reset.
  • The next valid slot begins at 05:45 PM.

Scenario 5: 24-Hour Cancellation Cutoff Enforcement

• Action: Parent with a booking for Sunday at 10:00 AM attempts to cancel on Saturday at 05:00 PM (17 hours prior).
• Expected Result:
  • Cancellation cutoff is configured at 24 hours.
  • System flags that the cancellation is inside the 24-hour window ($17 < 24$ hours).
  • A 50% cancellation fee is retained, and the seat is released back to the public inventory.