Aayush Garg
Co-Founder at Zappify
Delhi, India
Summary
🤩
Rockstar🎓
Top SchoolAayush Garg is a pragmatic founder and product-focused engineer with six years of experience building lean, scalable software for startups and enterprises. He co-founded Zappify after bootstrapping from just ₹150 and has since shipped 70+ custom products across five countries using no-code/low-code and custom stacks, delivering builds roughly 3x faster than traditional cycles. Comfortable as a hands-on ML/Flask developer and no-code engineer, he bridges technical execution with strategic CTO-style guidance—prioritizing ROI, scalability, and low technical debt for non-technical founders. His open-source work includes face recognition tooling and live data collection scripts, reflecting a solid applied-ML background that complements his product engineering practice. Known for turning early experiments into production-ready MVPs that help clients raise capital and automate operations, he combines street‑level hustle with repeatable delivery processes.
5 years of coding experience
3 years of employment as a software developer
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at Guru Gobind Singh Indraprastha University
Stackoverflow
11reputation
6kreached
5answers
0questions
Github Skills (27)
face-detection10
opencv10
python10
scikit10
scikit-learn10
computer-vision10
dlib10
k-nearest-neighbours10
windows-gui9
csv6
moviepy6
face-recognition6
git-pull6
bitbucket6
github6
Programming languages (11)
Github contributions (5)
akshitagupta15june/Face-X
Dec 2020 - Mar 2021
Demonstration of different algorithms and operations on faces. Star the repo⭐
Role in this project:
ML Engineer
ML EngineerContributions:69 commits, 14 PRs, 39 comments in 2 months
Contributions summary:Aayush contributed significantly to face recognition and related functionalities within the repository. They developed scripts for live data collection and image recognition using K-Nearest Neighbors, demonstrating an understanding of face detection, feature extraction, and machine learning model implementation. Additionally, the user created a GUI for the face recognition system, indicating involvement in the development of a user interface and integration of the recognition model. Furthermore, they implemented virtual makeup filters using computer vision techniques.
recognition-algorithmsapiup-for-grabsanimationpython
Aayush-hub/heAlthy-proGramMer
Jul 2020 - Oct 2021
Contributions:2 reviews, 22 commits, 9 PRs in 1 year 3 months
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