Human founder of Dhanur AI: AI employees for Indian businesses, and a company that runs itself on them. My team helps businesses work out what to automate, which AI employees would help, and what it would cost.
Now building
Where customers reach an AI employee
On website chat, chat links and email, and on WhatsApp in pilot.
AI employees follow up with the leads that come in.
They book the meeting with your team.
Anything risky waits for a person to say yes.
Every task shows what it cost, in rupees.
Run in the open
You can see the team and live figures from its systems on the company page, before you trust AI employees with your own customers.
Also building · Dhanur Content OS
Building the world’s cheapest content distribution & monetization ecosystem.
Dhanur Content OS turns research into shorts, longform, PDFs, courses, and digital assets — distribution, funnels, and monetization run by agentic workflows, so a tiny team ships studio-grade volume across 30 brands at the lowest cost structure in the market.
Shorts, longform, PDFs, and courses rendered from a single content pack — branded, captioned, and AI-disclosed.
Research, generation, review, and publication orchestrated by AI agents, with human approval on anything that matters.
Free lead-magnet → low-ticket asset → high-ticket course. Owned products and audiences — no ad dependency.
A portfolio of vertical publishers — real estate, law, finance, startups, and more — each its own mini-business.
Work with my team
If you run a business and want to know where AI fits, book a call with my team. We’ll look at how your business works today and help you work out what AI can take on.
You’ll chat with my AI assistant first, and it will book a time with my team.
Prefer email? nishgaba.ai@gmail.com
Which parts of your routine work are worth handing to AI.
For example, answering customers, following up leads or booking meetings.
The costs involved, so you can decide with the numbers in front of you.
About
I'm the human founder of Dhanur AI, which I started in October 2024. Dhanur AI builds AI employees for Indian businesses and runs itself on them: I set direction, approve what matters and work with customers, while our AI employees handle support, sales, product ideas and more. Its AI employees answer customers, follow up leads and book meetings, ask a person before anything risky, and show the rupee cost of every task.
Before Dhanur AI, I was a director of Prodigal AI Technologies from 2021 to 2025.
I have led engineering as CTO and technical lead across AI, security, and Web3 ventures spanning India, Singapore, the United States, and the United Kingdom — designing research, building teams, and turning frontier ideas into deployed products.
My current focus is autonomous multi-agent systems: frameworks that research, generate, review, and publish content end-to-end, now extending into multi-modal pipelines for images, short-form video, and full animated series.
“Great leaders know one thing: they don't know everything.”
“I speak math, probability, and occasional human languages.”
Dhanur AI
AI employees for Indian businesses: they answer customers on website chat, chat links, email and, in pilot, WhatsApp, and show the rupee cost of every task.
Multi-agent systems
Frameworks that research, generate, review, and publish content end-to-end.
Multi-modal pipelines
Images, short-form video, and full animated series.
AI-native publishing
Agentic workflows, courses, and digital assets across 30 brands in English and Hindi.
Projects
Showing 6 of 23 projects
Developed a high-speed facial recognition attendance system using a modified FaceNet combined with a facebox detector, optimized for edge deployments to ensure robust security and streamlined attendance tracking.
Engineered a real-time posture correction and repetition counting solution using OpenPifPaf, quantized to 8-bit for TensorRT on mobile edge devices, enabling accurate exercise guidance.
Customized and quantized MobileNetV2 to optimize training and inference for fish-eye camera systems, enabling real-time people tracking and threat-based object detection.
Built an automated scoring engine to streamline machine learning hackathon evaluations, ensuring fair and efficient project assessment.
Deployed hyperspectral imaging on Jetson Nano edge devices to assess crop health and soil moisture, optimizing irrigation strategies and promoting sustainable agriculture.
Engineered a vision-based solution for rapid fire and threat detection, leveraging on-premise and edge deployments to significantly enhance safety protocols.
Path
Oct 2024 – Present
India
Jan 2021 – Jun 2025
India
2024 – 2025
India
2022 – 2023
Singapore
2021 – 2022
USA
2021
Singapore
2018 – 2021
India
2017 – 2018
India
2022 – 2023
Community2022 – 2025
Community2016 – 2017
EducationScotland
2012 – 2016
EducationDelhi, India
Recognition
Uniswap V3 Technical Analysis
Credmark
Streamlining Choice of CNNs and Structure Framing of Convolution Layer
Springer
ALGOSAGE: An Introduction to Liquidity Providers & Backtesting Engines
ResearchGate
Bridging the Gap in COVID-19 X-ray Datasets: Stable Diffusion-based Synthetic Image Generation for Enhanced Diagnosis
JCRES
Enhancing Cloud Analytics with ZSEARCH: A Generative AI Chatbot for Real-Time Insights
ResearchGate
National AI Merit Award for Multi-Agent Systems Research
2024Confederation of Indian Industry (CII)
Contribution Award
2024Awarded by Delhi CM Ms. Atishi — recognized for contributions and recruitment efforts at GGSIPU
Scholarship for Higher Education (SHE)
2011Issued by CBSE, India — awarded to the top 1% in science nationally
Open source
Contact