Riyaz is an artificial intelligence-powered music education app that provides personalized feedback to users as they practice instruments. It has grown rapidly with over 5,000 daily active users and 10 million user recordings uploaded without any marketing spend. The app analyzes audio using machine learning models trained on expert reviews to assess users' fundamentals, intonation, timing and more.

1. Can we scale
art education?
Hint: Don’t get too subjective!

2. This is what we do

3. Founder of MTG-UPF
PhD at CCRMA, Stanford
Prof. Xavier Serra
Chief Research Officer
BTech and MS at IIIT-Hyd
PhD at MTG-UPF, Barcelona
Gopala K. Koduri
CEO
Team
Swapnil Gupta
Technical Lead
BTech at IIIT-Hyd
Masters at MTG-UPF, Barcelona

4. A music guru in your pocket!
Our USP is machine intelligence that provides human-like feedback

5. Traction so far
DAU | MAU
5 k | 80 k
Engagement per user
8 min / day*
Dec’16 Feb’17 Jul’17
10k
23k
200k
400k+
Downloads
● 10 million user recordings
● Everyday, riyaz == 300 full-time
teachers
Not a penny spent on this growth!
Oct’17

6. How does Riyaz work?
Content Management System
Automated content
transformation
Scalable content storage &
delivery platform
Courses
Live visualization as user
practices
Audio analysis and feedback
Cloud sync
Users
Riyaz
Teachers

7. How does Riyaz work?
Content Management System
Automated content
transformation
Scalable content storage &
delivery platform
Courses
Live visualization as user
practices
Audio analysis and feedback
Cloud sync
Users
Riyaz
Teachers

8. Audio Signal Processing
Fundamental
pitch
Loudness
Formants
Similarity
Intonation
Timing
Modulation
...

9. Building Machine Models
Seeding from experts
Predefined rubric
based reviews
Propagation

10. Infrastructure
Data
MySQL
(app data)
Object storage
(10m+ files)
Analytics
Big data cluster
for OLAP data
Data
visualization &
reports
Computation
Audio data
processing
Machine
learning

11. A music guru in your pocket!
A product of