MotoQuant started as a single question at a drag strip outside Pune: “How do I know which part will actually move my ET?” Every tuner, racer, and weekend warrior we talked to had the same problem. The answers were guesswork, YouTube comments, or ₹50,000 test runs. There had to be a better way.
Indian drag racing has exploded over the last decade. Aamby Valley, MMRT, BIC, Kari, Hyderabad — the strips are full. But the tooling hasn't kept up. Racers still tune by feel and magazine estimates. Tuning shops quote improvements from memory. Parts distributors can't tell you how much faster that exhaust will actually make you.
Meanwhile, the global sim tools that do exist are built for international bikes and international conditions. A tool calibrated for Santa Pod at 5°C doesn't tell you anything useful about Aamby Valley at 35°C and 1100 m density altitude in November.
MotoQuant is built specifically for the Indian drag scene — with Indian bikes (all 57 of the most common Indian-market machines), Indian parts prices in INR, Indian venues with real seasonal weather data, and Indian community benchmarks used for validation.
We could have built a regression. Train on a database of published ETs, predict new ones by interpolation. Fast to build, reasonable accuracy for common bikes.
But regressions break silently. They can't tell you why your R15 V3 is a second slower than predicted. They can't model the interaction between a new clutch kit and a heavier flywheel. They can't simulate what happens when you run the same bike at 5°C versus 38°C.
First-principles physics can. Every sub-model — Pacejka tire, Willans friction engine, RK4 integrator — produces physically interpretable outputs. When the model is wrong, we can find and fix the cause. When you add a part, the physics of that part propagates through the whole system.
Top-10 mean error after our July 2026 calibration pass: ±0.009s. Reference baselines pinned bit-identical across every commit. That's what first principles buys you.
Engineers first. Racers second. Shipping a tool we'd use ourselves.
The engineer who started MotoQuant and leads it — M.Tech from NIT Warangal, B.Tech from Manipal (Automotive System Design). He owns the physics: the vehicle-dynamics model, the calibration against real Dragy traces, and where the engine goes next.
Depth from both sides of the workshop door — CFD engine-combustion and magnetorheological-suspension research at NIT-W (plus a filed design patent) on one side; 25+ performance cars tuned by hand at Power Solutions Pune — Mercedes-AMG, BMW, Audi, Jaguar Land Rover — on the other. ECU-tuning certified.
Automobile-and-AI engineer — the software and machine-learning instinct behind MotoQuant's early architecture, from the simulation scaffolding to the first surrogate models and ROI ranker. Now a co-founder and advisor, still close to the technical direction.
Day to day he's building Dhisetu, an AI-assisted indie game studio in Bengaluru — a hardcore indie gamer, which is where the instinct comes from. His bet: the next studios won't be big teams but solo creators with AI co-pilots. Same instinct here.
Electrical engineer and our pitchman — finishing his B.Tech in EEE at Manipal. The growth-and-market side of MotoQuant, and the electronics half of the hardware roadmap: PCB design, EV powertrain and battery tech, low-level C.
Communication and market knowledge are the levers he owns, plus real market experience — turning a physics engine into something racers and tuning shops actually hear about, and want to implement.
“In my third year, a major bike accident paused my degree. While recovering, I refused to sit idle — I built a social-media audience and finished multiple industry-standard certifications. I don't just study engineering; I build, optimize, and execute under pressure.”
Roadmap — no specific dates, shipping when it's right
15 sub-models, 541 bikes, 593 parts, 20 venues, 4,393 tests. Full validation suite.
FastAPI backend, Next.js frontend live at motoquant.in. Dragy/dyno/ECU import + auto-calibrator.
Parts ROI knapsack, Bayesian build optimiser, XGBoost & DNN surrogates, Smart Recommendations.
Accounts + freemium tiers live (free during open beta). Razorpay + Stripe payment rails wired. Conversational AI tuning shipped. PPO launch control next.
Whether you're a tuning shop interested in the Pro plan, a racer who found a bug, or just want to talk drag racing — reach out.
No contact form, no ticket queue. Mail lands straight in the founders' inbox and we reply within 48 hours — usually much faster. Bug reports with a share link or a Dragy CSV attached get answered first.
Email motoquant@gmail.comreplies within 48h · IST working hours