नाविक्सर

Rebuilding this scene from raw points, the way Navixar rebuilds Indian streets

NAVIXAR

Every robotaxi company in the world skipped India.
Navixar is India's answer to the robotaxi revolution.

India-Native VLA-Powered Simulation-First

The world's robotaxi players have raised $21B+ and now operate in every major auto market but one. India, the world's 3rd largest auto market, still has zero. Navixar exists to be first.

RoundPre-Seed

InstrumentSAFE

Current Raise₹00 Cr

Target CloseQ4 2026

Request the data room Read the thesis ↓

Munish Raj · Founder & CEO · munish02@gmail.com · Strictly Confidential

Scroll to explore

01The Opportunity

$21.4B Raised. Not One In India.

The world is racing to build robotaxis. Waymo, Zoox, Waabi, Wayve, Baidu Apollo, WeRide, Pony.ai, Momenta: every major geography already has a credible autonomous player. India, the world's 3rd largest auto market, has none.

USA / Canada

Waymo (Alphabet)

$160B+ Valuation

3,000+ vehicles, ~500K paid rides/week across 10 US cities. Zero India presence.

Zoox (Amazon)

$1.4B raised · production-intent robotaxi

Canada

Waabi

$750M · Uber-backed

Canadian-founded, US-focused. North American highway AV. No Asia operations.

UK / Europe

Wayve

$1.3B · NVIDIA & Microsoft

Embodied AI approach. UK-focused testing. Emerging market expansion not on roadmap.

China

Baidu Apollo

$1.8B · 17M rides

China-specific. Structured road assumptions. No India presence.

WeRide · $1.44B Nasdaq

Momenta · $1.5B GM/Benz

Pony.ai · $1.22B Nasdaq

India

No Credible AV Player

₹0 Deployed

3M+ rides/day. Zero autonomous deployments. This is the gap Navixar was built to close.

Sources: Crunchbase Q1 2026 AV Sector Report · TechCrunch · Waymo/NHTSA filings Dec 2025 · Zoox 2026 · Waabi Jan 2026 · Wayve Series D 2026

प्रश्न

02The Question

$21B Everywhere Else. Zero In India. Why?

It's not because nobody noticed 1.4 billion people. Before we show you our thesis, take a guess: what are the two hardest technical problems in bringing autonomy to India? Pick two.

Select your two answers to unlock our thesis

सिद्धांत

03Our Thesis

Algorithms (AI Models) are becoming more accessible. Data and Validation are not.

Open-source stacks, foundation driving policies, and VLA architectures are converging fast, making the tech table stakes. What nobody has is Indian data, an India Compliant Simulator, and a real path to deploy in Indian traffic. That's the actual bottleneck, and it's the whole company.

Pillar 01 · Data

Collect Data No One Else Has

Drone capture, gamified crowdsourcing, and bulk dashcam acquisition are three ways to get Indian driving data fast, without waiting years on a sensor fleet.

Data Moat

Pillar 02 · Simulation

Validate At A Scale Roads Can't Match

Gaussian-splat reconstructions of real Indian streets let us stress-test millions of scenarios before a single vehicle drives one of them.

Simulation Moat

Pillar 03 · Deployment

Gain Attention with an In-House Self Driving Robotaxi Bot

Deploying a physical in-house robotaxi bot creates unmatched real-world presence, viral brand attention, and immediate validation across Indian cities.

Robotaxi Bot Navixar Robotaxi Bot Crashing Out

☕ Let's take a break

Stand In An Indian Junction
For One Minute.

A live junction: fruit cart, cows, autos, and nobody honouring a lane. You are the glowing blue dot. Move your cursor (or finger) and try to reach the green line at the top.

0 near-missesGoal: cross to the top ↑

What are you interested in?

Choose a path to explore the aspects of Navixar that matter most to you.

04The Problem

The World Solved Autonomy For Everywhere Except India.

India's roads and traffic are unlike anywhere else, and no existing autonomous stack, dataset, or simulator was engineered to navigate them.

The Data Gap

99%

of AV training data is Western. A model trained on San Francisco cannot handle Saidapet: 40+ vehicle types, cattle, and lane-less chaos are entirely absent from global datasets.

Source: Crunchbase 2025

Simulation Gap

Broken

Existing simulators model structured lanes and western traffic with hand-built meshes. India's potholes, unmarked roads, and unstructured intersections do not exist in any current simulation stack.

Source: MoRTHS Gazette 2024

The Market Gap

₹0

India has 3M+ Ola/Uber rides per day, representing the world's ideal robotaxi culture, yet zero commercial autonomous vehicle deployments exist. The whitespace is total.

Source: Ola/Uber India 2025

05Gap 01 · Data

Let's Brake It Down.
Here's What Makes India Unique.

डेटा

99%

of all AV training data originates in the US or Europe. Indian roads are invisible to every major autonomous driving model on earth.

Western Training Data99%

India-Specific Data<1%

What Makes India Different

40+ Vehicle Classes

Two-wheelers, auto-rickshaws, cattle carts, and BEST buses all sharing a 4-metre lane.

Livestock and Unpredictable Actors

Cattle, pedestrians, and vendors mid-road are routine occurrences, not edge cases.

Road Surface Variability

Potholes, broken asphalt, flooded lanes, and unmarked speed bumps that no western dataset captures.

Zero Lane Discipline

Five vehicles wide on a two-lane road is standard. No model trained on SF can reason about this.

06Pillar 01 · Data Collection

We Will Innovate And Collect Data.

India runs on the world's largest digital public infrastructure: a billion smartphones, UPI, cheap data. Navixar leverages that to crowdsource and gamify data collection, because the goal isn't just kilometres. It's diversity: every vehicle type, every merge, every impossible intersection. Diversity in traffic is the dataset nobody else can build.

Remember Pokémon Go?

Millions of Indians walked every street, alley, and corner of this country chasing Pokémon — and every step fed mapping data to a foreign company building the world's most accurate maps. India already crowdsourced a country-scale dataset once. It just didn't own it. This time, the game is ours, the streets are ours, and the data stays ours.

2 vehicles undetected

The Navixar Data Pipeline

Drone-Based Aerial Capture

Drones flying above the vehicle see the dynamics ground sensors miss, such as two-wheelers, pedestrians, and near-misses within 2 metres of the car.

Gamified Traffic Challenges

Players build traffic challenges for each other inside splat-reconstructed Indian streets. Every attempt to solve one becomes labelled training data.

Dashcam Footage Acquisition

Buying existing dashcam footage at scale is the fastest, cheapest way to bootstrap millions of kilometres of real Indian driving before a single Navixar vehicle hits the road.

Owned Pipeline = Moat

Three independent sources feeding one proprietary dataset. Every kilometre anyone drives on foot, by drone, or on camera makes the model better and harder to copy.

The insight: You don't need a fleet to out-data everyone. Drones, dashcams, and a game get there faster and cheaper than a garage full of sensor-laden cars.

Same Dataset. Two Ways To Get There.

Traditional sensor fleet (Waymo playbook)~$20M+ per city · 3–5 years

Navixar crowdsourced pipeline<$1M · months, not years

Every rupee goes into diversity of traffic, not metal on wheels. A crowd of a million phones sees more of India in a month than a fleet of ten sensor cars sees in a decade.

07Pillar 02 · Simulation

Gaussian Splats Make Large-Scale Validation Possible.

Mesh-based simulators approximate the world with hand-built polygons. Gaussian splats reconstruct it from real captured footage, keeping every pothole, glare, and reflection intact. That fidelity gap is what lets Navixar validate millions of scenarios before a single physical deployment.

Why Simulation-First Works

Infinite Scenarios

Millions of edge cases that would take decades to encounter on real Indian roads, all simulated at compute cost.

Orders of Magnitude Cheaper

One GPU cluster vs. a fleet of sensor-laden vehicles. Waymo spends $20M per car. Navixar spends compute.

Safe Iteration

Test sudden cattle crossings, brake failures, and flooded roads without any physical risk.

Validation At A Scale Roads Can't Match

Splat-based scenes are photoreal enough to trust the results. Every model update gets stress-tested against millions of Indian edge cases before a single real kilometre.

Mesh vs. Gaussian Splat

Mesh-Based Simulators (CARLA, Waymo Sim)

Hand-built polygons and textures. Structured US/European traffic, 4-way intersections, lane markings. Indian roads are invisible.

Mesh-Based Simulators (LGSVL, Apollo)

Chinese-road-optimised meshes. Misses Indian textures, pothole dynamics, and chaotic merges entirely.

Navixar's Gaussian Splat Engine

Reconstructed from real captured footage: actual potholes, actual glare, actual chaos. Validation on a splat scene is validation on the real road.

Processing Environmental Data...

Rendering structured lanes & basic polygons...

Move mouse to explore environment

08Our Solution · Simulation

The Simulation Environment Tailored for India

Current simulators focus on lanes and structured traffic. India brings challenges in roads, textures, and unknown objects that no existing tool handles.

Pillar 01

Road Fidelity

Pothole meshes, broken asphalt textures, flooded sections, and unmarked speed bumps. Every Indian road imperfection captured by drone and dashcam, then simulated with Gaussian splat rendering.

Gaussian Splat

Pillar 02

Traffic Chaos Engine

40+ vehicle types with behavioural models calibrated on Indian driving data. Lane-less merging, sudden cuts, pedestrians ignoring signals, livestock, and roadside vendors.

Stochastic Agent Modelling

Pillar 03

Gamified Data Flywheel

Users build and solve traffic challenges inside splat-based Indian environments as a game. Every decision becomes training data, generating scale without fleet infrastructure cost.

Crowdsourced Training Loop

Crowdsourced scale

The Gamified Training Loop

Instead of spending hundreds of millions on test drivers and fleets, Navixar gamifies the training process. Players create traffic challenges for each other to solve inside real, reconstructed Indian roads. Every maneuver, deceleration, and path choice feeds straight into our path planning AI.

Navixar Gamified Data Collection Mobile App Dashboard Mockup

☕ Let's take a break

You Be The Perception Model.

For 25 seconds, do the job our AI does every millisecond: click or tap everything that crosses the road to label it. Fair warning — almost none of these classes exist in Western training data.

0 labelled25s0 missed

09Why This Team

Built By Someone Who's Already Sold This To India's OEMs.

Data collection and processing isn't a hypothesis for Navixar's founder: it represents seven years of shipped work.

Munish Raj has spent seven years inside India's automotive data and simulation industry. Across OEM engagements, one thing has been consistent: data collection and processing is the easiest, most repeatable sell in the room. Every OEM needs it, and almost none can build it well in-house. Navixar takes that exact wedge and pushes it one notch further: from selling data as a service, to owning the full data-to-deployment stack.

7 Years

Inside The Industry

Seven years building data collection and simulation pipelines for automotive OEMs in India, the same buyers Navixar now sells a full autonomy stack to.

Domain Authority

10 Teams

aBaja SAE India

Rallied 10 student engineering teams to attack the automated-driving problem statement at aBaja: proof the problem is tractable with the right structure.

Grassroots Proof

SIH

Smart India Hackathon

Personally got Automated Driving added as an official Smart India Hackathon problem statement, placing the same problem in front of the country's entire engineering talent pipeline.

National Reach

10Why Now: The Evidence

The Robotaxi Race Just Went Global.
India Is The Exception.

Signals from across the industry over the last few months show that the race is accelerating everywhere but here.

A Governed Path Now Exists

The UN adopted the first binding global regulation for fully autonomous vehicles, effective January 2027, requiring mandatory simulation, testing, and safety-data recording for every signatory market.

Source: UNECE, 2026

Robotaxis Are Now Manufactured, Not Prototyped

Zoox unveiled a production-intent robotaxi with 100 vehicles/week manufacturing capacity. Waymo runs 3,000+ vehicles and ~500K paid rides a week across 10 US cities.

Source: Zoox · Waymo/NHTSA filings, 2026

The Unbundled Playbook Is Working

Bolt + Pony.ai + Stellantis launched a driverless "Living Lab" in Luxembourg; LOXO is running driver-out operations in Bern. Vehicle, AI brain, and demand network no longer need to be one company.

Source: Bolt · LOXO, 2026

Autonomy At Delivery Scale, Today

10,000+ driverless delivery vans now operate daily across China via Cainiao, DiDi, and Neolix, proving autonomous fleets already run at real operational scale.

Source: A3 Market Intelligence, 2026

Gaussian Splatting Is Becoming The Standard

NVIDIA's AlpaGym and NuRec, and Cesium's native splat streaming, are turning the exact simulation technique Navixar is built on into shared industry infrastructure.

Source: NVIDIA · Cesium, 2026

An OEM Insider Is Saying It Publicly

Maruti Suzuki's own Head of ADAS Testing says global playbooks don't automatically work on Indian roads, and calls for an India-first development strategy.

Source: LinkedIn, Head-ADAS Testing, Maruti Suzuki, 2026

बाज़ार

11The Market

This Market Is Measured In Billions, Not Rides.

3M+ daily rides was the volume story. Here is the money story: three overlapping markets, all growing, all with zero autonomous players in India.

$24B

India taxi & ride-hailing market, 2026

Source: Mordor Intelligence 2026

$14.7B

India autonomous trucks market by 2031, at 23.1% CAGR

Source: Mobility Foresights 2025

$400B+

Global robotaxi market by 2035

Source: Goldman Sachs 2025

The Addressable Pyramid · hover each layer

TAM$35B+India mobility & autonomy spend

SAM$6–8BAutonomy-addressable by 2031

SOM$150–300MNavixar's 5-year capture

Hover a layer to see how the number is built.

Why India Is the Perfect Launch Market

+Highest ride-hailing density globally: demand is already proven

+2.2M truck-driver shortfall — 55 drivers per 100 trucks — costing the economy ~$60B/yr

+Government actively building an AV testing and deployment framework

+Consumers already trust app-based transport for daily commutes

+If it works in India, it works in every emerging market on earth

The Competitive Moat

Waymo spent $3.5B with zero India presence. Mobileye and Baidu have global reach, but neither has India-native training data, local regulatory access, or a deployment roadmap for unstructured Indian traffic.

First-mover data advantage compounds. Every kilometre driven by drone, by dashcam, or by a player inside the game makes the model better for India, and only Navixar owns that data.

Sources: Mordor Intelligence India Taxi Market 2026 · Mobility Foresights India Autonomous Trucks 2025 · Goldman Sachs Research 2025 · Grand View Research India AV Outlook 2030 · TruckMitr / IRU driver-shortage estimates 2025

गणित

12Unit Economics

80% Of Every Fare Goes To The Driver.
Autonomy Rebuilds That Entire Stack.

Under India's MVAG 2025 rules, aggregators keep at most 20% — at least 80% of every fare flows to the driver. But that 80% isn't wage: the driver pays for fuel, the vehicle EMI, and maintenance out of it. Autonomy doesn't just remove a salary. It replaces the entire human cost stack with machine economics — EV energy, amortised hardware, and compute that gets cheaper every year. This model is interactive: drag the sliders, stress-test our maths.

Fare ₹20/km

Robotaxi vehicle + sensors ₹22L

Utilisation 250 km/day

Human-Driven Ride · today

The platform's 20% cap is the only margin available — the other 80% is consumed by the driver's fuel, EMI, maintenance, and living.

Navixar Autonomous Ride · EV robotaxi

Every cost line here is machine economics: it falls with scale, utilisation, and compute prices. Wages only ever rise.

—Autonomous cost / km

—Margin / km at today's fare

—Margin %

—Vehicle cash payback

Illustrative model — assumptions editable above; vehicle amortised over 250,000 km. Benchmarks: MVAG 2025 (≥80% of fare to driver) · Waymo ~$1.98/mile vs US ride-share ~$2.00/mile today, projected → $0.25/mile by 2035 (Morgan Stanley / Goldman Sachs 2025).

दृष्टि

13The Business

The Robotaxi Is The Story.
The Ladder Is How We Fund It.

We don't burn a decade of capital waiting for public-road approval. Each rung of the ladder generates revenue, data, and regulatory proof — and pays for the next.

The Momenta Playbook — proven at $9B

On July 8, 2026, Momenta lists in Hong Kong at a $9B valuation. Its model: license the driving stack to OEMs — GM, Mercedes-Benz, BYD, Toyota — at roughly $500–1,500 per vehicle, and use that high-margin recurring revenue (65% of its $354M 2025 revenue, growing 82% YoY) to fund the Level-4 robotaxi program. Navixar runs the same two-leg play, tuned for India — with a rung Momenta never had: a driver crisis that makes controlled-environment autonomy an immediate, desperate purchase.

The Revenue Ladder · click each rung

Rung 01 Controlled Environments — Ports, Mines, Logistics Yards 2027–28 · first revenue ▾

55 : 100drivers available per 100 trucks in India — a 2.2M driver shortfall costing ~$60B/yr

$4.25B → $14.7BIndia autonomous trucks market by 2031, 23.1% CAGR (Mobility Foresights)

Why this rung is first: geo-fenced private land needs no public-road approval — deployment can start the moment the stack works. Buyers have brutal ROI maths: 25–30% of truck fleets sit idle for want of drivers. Revenue: per-site deployment contracts + annual per-vehicle software fees. Every autonomous kilometre also feeds the data moat.

Rung 02 OEM Stack Licensing — India's Momenta 2028–30 · recurring royalties ▾

4M+cars sold in India annually (SIAM) — with zero India-native ADAS/AD stack on offer

$500–1,500per-vehicle royalty benchmark from Momenta's OEM licensing leg

Why OEMs buy from us: Tata, Mahindra, and Maruti need ADAS that understands Indian roads — global stacks trained on lane discipline fail here. Maruti's own Head of ADAS Testing says so publicly. Development contracts first, then per-vehicle royalties: high-margin, recurring, and it compounds with every model year.

Rung 03 The Robotaxi Fleet — The Story 2030+ · the prize ▾

3M+ride-hailing trips per day in India, today, with zero autonomous supply

$400B+global robotaxi market by 2035 (Goldman Sachs) — India's share is unclaimed

The prize the ladder pays for: per-ride revenue at the unit economics you stress-tested in Chapter 12 — machine costs against fares built for human costs. Launched corridor-by-corridor in metros, with regulatory proof and data compounded from rungs 1 and 2. Beyond India: Southeast Asia, Africa, and Latin America share our road DNA.

Sources: Bloomberg / Reuters, Momenta HK IPO June 2026 · Momenta prospectus reporting · SIAM · Mobility Foresights 2025 · Goldman Sachs Research 2025

14Milestone Maths

No Hockey Sticks. Ranges, Tied To Milestones.

Pre-revenue projections are fiction with a spreadsheet. What we commit to instead: each milestone unlocks a revenue range, and each range funds the next milestone. Tap a card to see the assumptions behind it.

2027

₹2–5 Cr

First paid controlled-environment pilot: one port or logistics-yard site, deployed and invoiced.

Assumptions

One site, 5–10 autonomous terminal vehicles. Deployment fee + per-vehicle annual software. Benchmark: enterprise autonomy pilots globally price at $250K–$600K per site. Sales cycle 6–9 months, so conversations start at close.

2028

₹10–25 Cr

2–3 controlled-environment sites live + first OEM development contract signed.

Assumptions

Site contracts repeat at ₹2–5 Cr each with 80%+ gross margin on software. OEM development contracts benchmark at ₹5–15 Cr (Momenta's "technical development services" leg pre-royalty). One OEM converts from the founder's existing 7-year relationships.

2029

Series A on proof

OEM royalty LOI + MoRTHS public-road testing application + robotaxi corridor demo.

Assumptions

By 2029 the company has revenue, an OEM logo, and regulatory progress — the three things that price a Series A. Comparable path: Momenta raised its growth rounds after OEM contracts, not after robotaxis. The robotaxi corridor pilot is funded by that round, not this one.

Illustrative ranges, stated as commitments to milestones rather than point forecasts. All figures pre-validation; assumptions shown per card.

☕ Let's take a break

A Quick Round Of Vyapar.

Every Indian childhood had the Monopoly clone — Vyapar, Business, the board with Bombay and Madras on it. Here's the autonomy edition. Roll the dice. Whatever square you land on, watch who collects.

GO ▸Pre-Seed Closes

Chennai Port YardRent ₹3 Cr

Driver ShortageEvent

OEM Royalty · TataRent ₹4 Cr

Chance: GPU Prices FallEvent

Mumbai Logistics YardRent ₹2 Cr

MoRTHS ApprovalEvent

Data RentRent ₹1 Cr

Bengaluru Robotaxi CorridorRent ₹5 Cr

Stuck In TrafficEvent

Maruti Dev ContractRent ₹6 Cr

Emerging-Market ExportRent ₹3 Cr

VYAPARThe Autonomy Edition

⚄

Stack owner's treasury₹0 Cr

Land anywhere. The stack owner collects.

15Tailwinds

Here Is What Else Is Going for Us

The infrastructure is in place. The talent exists. The regulation is moving. The capital is arriving. We are timing this exactly right.

Existing ADAS Ecosystem

An underserved ADAS engineering community in India, with no domestic OEMs deploying at scale. World-class engineers exist. Navixar captures this talent at day-one cost.

Engineering Talent

Graduate Talent Surplus

IIT and NIT graduates specialising in robotics, AV, and AI, with nowhere to apply it in India. World-class technical talent at Indian salary scales.

Talent Pipeline

EV Supply Chain Investment

Tata, Ola Electric, and the FAME II subsidy scheme are building EV infrastructure at scale. AV-ready electric platforms will follow. Navixar rides this wave.

EV Infrastructure

Regulatory Tailwind

MoRTHS AV testing and deployment framework (2024 gazette notification). India is actively building the legal path for autonomous vehicle deployment on public roads.

MoRTHS Framework 2024

Deep Tech Capital Is Flooding In

India's deep tech startup funding is growing at its fastest pace ever, with investors actively hunting for hard-tech, India-first bets.

Deep Tech Wave

Built For India's AI Mission

India's national AI push isn't just about generic models. Autonomous driving for unstructured Indian roads is a flagship, India-only problem, solved with an India-first mindset.

India AI Alignment

Compute Only Gets Cheaper

GPU and edge-compute costs keep falling every quarter. A simulation-first, compute-heavy strategy gets more viable, not less, the longer this plays out.

Deployment Tailwind

16The Next 24 Months

From Raise To Road: Guess The Timeline.

Every phase de-risks the next. Data before simulation, simulation before models, models before metal. But how fast? For each milestone, guess when we hit it — then see the actual plan.

0 / 5 guessed

Close Pre-Seed · Assemble The Core

Founding team of 5 focusing on perception, simulation, and data engineering. First dashcam-footage acquisition partnerships signed. Drone capture pilots begin in one city corridor.

Foundation

Your guess:

1M+ km Of Indian Driving Data

Dashcam pipeline at scale, drone capture across 3 city corridors, gamified crowdsourcing loops live. First Gaussian-splat reconstructions of real Indian streets, forming the seed of the simulator.

Data Moat Begins

Your guess:

Simulation Engine v1 + Gamified Beta

Splat-based simulator running Indian chaos scenarios. Gamified data app in public beta, accelerating the crowdsourced flywheel.

Simulation Moat

Your guess:

India-Native Driving Model v1

First VLA policy trained on the proprietary Indian dataset, validated against millions of simulated scenarios. OEM pilot conversations formalised into an LOI.

Model Milestone

Your guess:

Closed-Course Demo → Seed Round

Autonomous demonstration on a closed Indian course. MoRTHS testing application filed. Raise the seed on proof, not promise.

Proof Of Autonomy

Your guess:

वापसी

17The Return

Every Major Market's AV Leader Is Worth Billions.
India's Seat Is Empty.

This is what the market pays for a national AV champion — companies that were pre-seed less than a decade ago. Hover the bars.

Waymo · USA

$160B+

Momenta · China

$9B

Wayve · UK

$8.5B

Pony.ai · China

$3.5B

WeRide · China

$1.8B

India · ?

Unclaimed

Hover a bar for the story behind the number.

Who Buys, If Not IPO

+Indian OEMs building autonomy gaps: Tata, Mahindra, Maruti Suzuki

+Global Tier-1s with India M&A desks: Bosch, Continental, ZF

+Global AV players needing an emerging-markets stack and dataset

+Ride-hailing platforms buying their autonomous supply: Ola, Uber

The Pre-Seed Return Case

Momenta was founded in 2016 and lists at $9B in 2026 — a decade from seed to IPO on the exact licensing-funds-robotaxi model. Wayve went from research lab to $8.5B in eight years without meaningful revenue.

The pattern: each major market prices in exactly one AV champion at billions. India's is the last seat open, and it costs ₹27 Cr to sit down at the table.

Sources: Waymo valuation reports 2025–26 · Bloomberg/Reuters Momenta HK IPO June 2026 · TechCrunch Wayve tender June 2026 · Nasdaq market caps, July 2026 (Pony.ai, WeRide)

18The Ask

Pre-Seed: $3.2M To Build The Moat.

SAFE instrument, targeting close in Q4 2026. Every dollar goes toward the assets nobody can copy: the dataset, the simulator, and the bot. This budget is interactive — flip the toggles, watch the total move, and see exactly what takes a hit.

Engineering Team · 3 years$1.0M

Perception, simulation, and VLA engineers from India's ADAS and robotics talent pool. Three full years of the only asset that builds everything else.

The Robotaxi Bot$150k

Battery pack, compute hardware, and an attention-grabbing bot India can't ignore. Pillar 03 made physical.

Model Training$500k

The VLA policy trained on the proprietary Indian dataset. The classic trade-off: rent the compute or own it.

Data Collection$500k

Cloud ingestion costs, drone permissions, and deploying the gamified crowdsourcing loops across Indian cities.

Simulator$500k

The Gaussian-splat simulation engine: India's chaos, reconstructed and replayable at validation scale.

Office, Legal & Misc · 2 years$100k

Office space, company setup, MoRTHS engagement, drone-operation compliance, and everything unglamorous that keeps the lights on.

Runway Buffer · 15% contingency$413k

Deep tech never ships on schedule. The buffer guarantees two full years of runway even when it doesn't.

Every robotaxi company in the world skipped India. Navixar is India's answer to the robotaxi revolution.

$21.4B Raised. Not One In India.

$21B Everywhere Else. Zero In India. Why?

Algorithms (AI Models) are becoming more accessible. Data and Validation are not.

Stand In An Indian JunctionFor One Minute.

What are you interested in?

The World Solved Autonomy For Everywhere Except India.

Let's Brake It Down.Here's What Makes India Unique.

We Will Innovate And Collect Data.

Gaussian Splats Make Large-Scale Validation Possible.

The Simulation Environment Tailored for India

The Gamified Training Loop

You Be The Perception Model.

Built By Someone Who's Already Sold This To India's OEMs.

The Robotaxi Race Just Went Global.India Is The Exception.

This Market Is Measured In Billions, Not Rides.

80% Of Every Fare Goes To The Driver.Autonomy Rebuilds That Entire Stack.

The Robotaxi Is The Story.The Ladder Is How We Fund It.

No Hockey Sticks. Ranges, Tied To Milestones.

A Quick Round Of Vyapar.

Here Is What Else Is Going for Us

From Raise To Road: Guess The Timeline.

Every Major Market's AV Leader Is Worth Billions.India's Seat Is Empty.

Pre-Seed: $3.2M To Build The Moat.

Every robotaxi company in the world skipped India.
Navixar is India's answer to the robotaxi revolution.

Stand In An Indian Junction
For One Minute.

Let's Brake It Down.
Here's What Makes India Unique.

The Robotaxi Race Just Went Global.
India Is The Exception.

80% Of Every Fare Goes To The Driver.
Autonomy Rebuilds That Entire Stack.

The Robotaxi Is The Story.
The Ladder Is How We Fund It.

Every Major Market's AV Leader Is Worth Billions.
India's Seat Is Empty.