TVS: VR Training & Assessment
Immersive Training and Assessment with Virtual Reality for Service Technicians
Automobile · India · VR App · Service Technician Training · Safety & Maintenance Built for TVS Motor Company’s Service & Training

75+
3D Assets

22
Action Steps
Mapped

35
VR Steps
Digitised

0
Setup
Time

3
Core
Modules

4
Months
Project Duration

What We Heard
From Stakeholders
-
Training and assessments take time to schedule and coordinate.
-
Access to vehicles and rigs is limited during peak operations.
-
Skill levels vary across locations and technician experience levels.ng hands-on training are a concern.
-
Safety during early-stage training is a concern.
From Users
SERVICE TECHNICIANS
-
Practicing directly on vehicles feels risky during early learning.
-
Fault scenarios are not always available during assessments.
-
Step clarity and sequence matter during complex procedures.
Challenges
The Users
Our Approach

Discover
Mapped workflows

Design
Built realistic VR

Validate
Validated onsite
Design Direction
Experiential Learning Principle
Technicians actively performed service procedures in VR rather than passively consuming instructions.
Cognitive Load Theory
Guided steps, contextual prompts, and focused interactions reduced mental effort during complex service tasks.
Error Prevention
Risk-free simulations allowed technicians to learn and practice procedures without live vehicle exposure.
Consistency & Standards
Training flows mirrored real TVS service processes, ensuring familiarity and repeatable learning outcomes across locations.

The Field Reality
We conducted onsite visits across TVS service and training facilities to observe real workflows, map safety checkpoints, and validate VR training and assessment scenarios.


Outcomes Achieved
The immersive VR solution enabled faster technician readiness through repeatable, safety-first practice and instant assessments. Standardised procedures reduced variability across service centers, while zero-setup deployment supported consistent capability checks without live vehicle dependency.

























