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Arunkumar Arunagiri LinkedIn

For owners of human-driven fleets

You have the fleet. What’s your robotaxi plan?

I help fleet owners assess the robotaxi opportunity: where to enter, which developers to pursue, and what their sites and operations need to become.

I'm Arun, co-founder of TARS AI. I worked on a purpose-built autonomous vehicle, and I now focus on the operation that has to run around one.

Email contact@tarsai.co Explore the work

Role: Co-founder and Co-CEO, TARS AI
Focus: Scaling autonomous fleet operations
Base: San Francisco Bay Area

Background

From 0 to 1. Now focused on 1 to N.

Much of my career has centered on bringing new technology into the world: embedded systems, aircraft software, cloud infrastructure, banking applications and a purpose-built autonomous vehicle. Along the way, I’ve led innovation labs across technology, healthcare and banking, working from early concepts through development and deployment.

That is 0 to 1: getting something new to work for the first time. What draws me now is 1 to N: taking technology that works and building the operation that lets it scale. For autonomous fleets, that means bringing sites, charging, maintenance, people and software together as one system.

Work with me

Decide where robotaxis fit in your fleet business.

You have vehicles, sites and people. Where do those assets fit in a robotaxi business? Which developers should you pursue? What would your operation need to change?

I help fleet owners work through those decisions and develop a plan around their markets, sites and existing business.

Choose where to enter

Assess your markets, potential developer partners and the business case, so you can decide where to focus your effort and investment.

Know what your first site needs

Work through layout, charging, staffing, turnaround and operational handoffs to identify what needs to change before deployment.

Plan the mixed years

Set out how human-driven ICE, EV and autonomous vehicles will share sites, infrastructure and people as your fleet changes.

Start with the decision in front of you.

Tell me your fleet type, the markets you operate in and the question you need to resolve. In our first conversation, we’ll identify where advisory work could help. We’ll agree the scope and outputs before work begins.

contact@tarsai.co

Email your fleet type, the markets you operate in and the question you need to resolve.

The lens

The car is autonomous. The operation around it is not.

Someone still has to charge it, clean it, fix it and recover it from the roadside, on a clock set by rider demand. Fleet owners already do most of that work every day. What changes is that there is no driver to move the car, spot a problem or fill a gap, so the operation has to be designed to run without one.

Plan for the mixed years.
Human-driven and autonomous vehicles will share your sites for years. Infrastructure and staffing decisions need to account for that transition.
Design the depot as one system.
Charging, cleaning and inspection affect the same outcome: when a vehicle is ready to return to service. Plan those steps together.
Choose partners against operating requirements.
Compare vehicle needs, launch markets, turnaround expectations and economics with what your operation can deliver.

TARS AI

An operation as autonomous as the vehicles themselves.

I co-founded TARS to build physical AI for fleet operations. We’re developing AI agents to coordinate operational decisions, with robotics for routine physical work.

An operating vision for coordinating the vehicle lifecycle and the people, infrastructure and services around it. Hover or tap a stage to see what supports it.

Which car should charge next? What work does it still need? Can it get back to riders before demand peaks? The agents weigh those questions together.

We start with a human in the loop. Agents recommend; operators approve or override. We record what was recommended, why, and what the operator decided. That record gives us a foundation for improving the agents and checking their behavior as more decisions become autonomous.

The goal: more cars carrying riders when demand peaks, less time lost between rides, and each person able to support more of the fleet. That is the economics behind the ambition: an operation as autonomous as the vehicles themselves.

See the TARS operating model

The series

The 1 to N series

Short videos on the operational questions behind autonomous fleets: the people, decisions and systems that keep cars ready for service.

All episodes on YouTube

Contact

What decision is in front of your fleet?

Email contact@tarsai.co with your fleet type, the markets you operate in and the question you are working through. That gives us a useful place to start.

Follow along on LinkedIn, YouTube and TikTok for practical perspectives on robotaxi economics, fleet operations and scaling physical AI.