Input Signals
Product · Engineering · QA · Customer · Data
I bridge product, engineering, QA, customer success, and data teams — turning ambiguity into execution.
I use AI tools to build prototypes, document systems, and test product ideas faster.
Current direction
Public builds showing how I use AI tools to turn ideas into usable prototypes, operational workflows, civic tools, and product demos.
A holographic AI companion built on Claude.
Pixel-accurate eye animations, four conversation moods, voice input/output, live camera feed, and a Jarvis-style HUD with diagnostics.
Why it matters: explores expressive AI interfaces through voice, mood, animation, and live interaction.
A Claude-powered Telegram bot for official Indian statistics.
Connects users to seven official datasets including PLFS, CPI, WPI, NAS, IIP, ASI, and ENV.
Why it matters: makes government statistics faster to access, understand, and cite.
Snap a gym machine. Understand what it is.
A vision tool that identifies gym equipment from an image and turns everyday confusion into quick understanding.
Why it matters: shows how a small real-world friction point can become an AI product idea.
A Claude-powered legal-rights advisor for gig workers.
Helps gig workers understand rights, legal protections, welfare schemes, grievance paths, and earnings scenarios.
Why it matters: turns legal and welfare information into clearer next steps for workers.
Operating practice
My professional work sits between product intent, engineering execution, QA feedback, customer needs, and data workflows.
AIMonk Labs Private Ltd
I work across engineering, QA, product, customer success, and data teams to resolve bottlenecks, improve workflows, and support reliable product execution.
AIMonk Labs Private Ltd
I helped build the in-house data operations function from the ground up, scaling the team from 0 to 6 members and creating foundational SOPs for future growth.
AIMonk Labs Private Ltd
I worked on deep learning models for an Intelligent Video Analytics ecosystem, using computer vision techniques such as face recognition, object detection, and OCR.
Execution foundations
Compact proof of the product ownership, agile delivery, and project execution foundations behind the work.
Scrum Alliance
Focus: product ownership, backlog thinking, stakeholder alignment, agile delivery.
View CredentialStructured project execution, agile delivery, and planning discipline.
Builder roots
Before GenAI became mainstream, I was already experimenting with computer vision, hardware, embedded ML, Raspberry Pi, Arduino, and technical writing.
Hands-on demos
Video proof from the earlier builder phase: hardware control, embedded ML, interface experiments, and public demos.
A hardware experiment exploring brainwave control and robotics through a four-wheel bot demo.
Connects embedded systems, machine learning, interface design, and practical experimentation.
Early credibility
Early technical credibility through international conference proceedings, a government-funded college project story, technical presentations, and publications.
A technical project that grew from a presentation in front of 150 people into department reviews, college leadership presentations, Government of Karnataka funding, and two international papers.
Published in the proceedings of the International Conference on Microwave Antenna Propagation and Remote Sensing 2014 in Jodhpur, Rajasthan.
Public learning
A compact archive of technical writing across Raspberry Pi, computer vision, TensorFlow, OpenCV, embedded AI, home automation, and dataset workflows.
Community
The CCCL Bangalore / Claude event as public proof: sharing AI experiments, build stories, and companion interface learning with a technical community.
I shared Claudy, an animated AI companion built with Claude, and connected the build story to AI companions, interface experimentation, and public learning.
View Related Link
Let's Connect
Find me where I share experiments, build logs, and ideas.