Founder Spotlight: Avneesh Agrawal, Netradyne Founder & CEO

Driving Vision—Avneesh Agrawal’s Journey From Qualcomm to Founding Netradyne

Road safety has always been a priority. But today, with insurance and repair costs rising sharply, it’s no longer just a safety issue — it’s an operational necessity for any business that runs a fleet, large or small. That’s why advanced fleet safety solutions powered by edge computing and artificial intelligence are becoming essential.

Netradyne is leading the way in computer vision-based fleet safety. By processing data directly at the vehicle (on the edge), Netradyne can instantly analyze driver behavior, road conditions, and potential hazards — delivering real-time feedback to drivers and helping to reduce the risk of accidents.

With over 20 billion miles of driving data processed from across the U.S. and around the world — in every type of weather and road condition — Netradyne’s AI-driven platform continuously identifies patterns and assists with driver performance optimization.

We recently spoke with Avneesh Agrawal, Netradyne’s founder and CEO, about how the company is building what he calls the perception stack for autonomous driving.

What inspired you to start Netradyne?

As an entrepreneur, I’ve always believed that breakthrough companies emerge when you spot the convergence of powerful trends — and act decisively.

In 2014, after years at Qualcomm Technologies, Inc., where I had the privilege of being deeply involved in mobile technology, I started noticing a few transformative shifts. First was edge computing — the ability to bring meaningful compute power to the device itself. Second, camera sensors were becoming highly affordable, making it possible to embed vision into everyday devices. And third, deep learning was moving out of academia and into practical, commercial use cases.

That convergence sparked our aha moment: what if we could combine edge computing, vision, and AI to solve real-world problems?

We founded Netradyne to explore that possibility. The name reflects our purpose — Netra means “vision” in Sanskrit, and dyne is Greek for “force” or “power.” Netradyne is, quite literally, the power of vision.

At first, we were drawn to the promise of autonomous driving, but quickly recognized a limitation — the technology simply wasn’t ready to fully replace human drivers. Then we had a second breakthrough: instead of replacing drivers, we could empower them. By applying computer vision and AI at the edge, we could analyze road conditions, driver behavior, and hazards in real time — and provide immediate feedback to help them improve.

“That realization became our mission: to make the road safer today, by enhancing human performance with the power of vision and intelligence at the edge.”

Since then, Netradyne has processed over 20 billion miles of driving data in diverse conditions across the globe. And we’re just getting started.

What differentiates Netradyne from competitors offering advanced driver and fleet safety solutions?

Trust is the foundation for changing behavior — especially when it comes to driver performance.
If drivers don’t trust your system, they won’t listen, and they won’t act. That’s why at Netradyne, everything we do is built around earning and maintaining driver trust.

It starts with accuracy.
False alerts destroy credibility. That’s why our AI is built to recognize real-world complexity. Take stop signs — most people think there’s only one type, but there are thousands of variations. Or imagine a stop sign with a police officer waving a driver through — our system understands that context and doesn’t penalize the driver. We don’t believe our competitors can make that distinction. 

Second, you need complete visibility.
Partial data leads to skewed assessments. Our solution performs 100% edge processing — analyzing every second of drive time, across every aspect of behavior. Nothing is missed.

Third, we emphasize positive reinforcement.
While we absolutely flag unsafe behaviors, our core focus is recognizing safe driving moments. We highlight good decisions — like a driver slowing down and yielding during a difficult merge — moments where a potential risk was avoided through smart, responsible behavior. That level of detail is only possible because our system runs the same perception stack as autonomous vehicles.

And we back it all with data no one else has.
We’ve processed over 20 billion miles of anonymized driving data — and we’re adding 700 million more each month. This isn’t just GPS data. We track the trajectory of every object, read over 100 types of signs, and understand full visual context. That lets us generate incredibly accurate risk assessments, including a driver’s GreenZone Score — a proprietary metric that correlates directly with accident reduction.

With enough historical data, we can now tell a new customer: “Based on your drivers’ GreenZone Scores, here’s your estimated accident rate per million miles.”
It’s a powerful moment — and it’s always followed by the same question: “How did you know that?”

“That’s the power of trust, technology, and data — working together to drive real change.”

What kind of impact are your customers seeing?

Across our customer base, we’re seeing a 40–50% reduction in accidents — and that includes some of the largest fleets on the road today.

What’s even more compelling is the cost. For less than the price of a monthly cell phone subscription per vehicle, these companies are cutting their accident rates in half. That alone delivers a 10x return on investment — and that’s just the tangible cost savings.

But the real impact goes even deeper. Research shows that intangible costs — like employee morale, brand reputation, and long-term medical issues — can be 2 to 2.5 times higher than the direct costs of an accident.

And there’s another key connection: safe driving strongly correlates with better fuel efficiency. When you put it all together, the value compounds — which is exactly why we’re seeing adoption accelerate across industries.

What’s in the pipeline for Netradyne?

We’re committed to continually pushing the boundaries of fleet safety. So far, we’re seeing up to a 50% reduction in accidents across our customer base. In fact, most customers achieve a 40–50% reduction within the first 12 months.

But that also means there’s still room for improvement — and a significant opportunity to impact the remaining 50%. That’s where our focus is heading next.

Beyond advancing our AI algorithms, we are extending that intelligence around the entire vehicle with a new product we call AI 360 — and customer interest is high.

We’re also exploring adjacent technologies that support broader fleet needs. For example, with Driver•i One, we offer a full-stack solution that combines advanced fleet safety with fleet management capabilities — all in one platform. 

What are some challenges you’ve faced in scaling the company?

Transitioning from a large company to a fast-scaling startup teaches you very quickly that many of the systems and processes you once took for granted simply don’t exist yet.

At a company like Qualcomm, things just happen — you decide to ship a product, and the infrastructure is already in place. The logistics, support, and supply chain are all seamlessly handled behind the scenes.

But in a high-growth startup, scaling operations becomes one of the biggest challenges. That was a key learning for us. We always knew we could build a great product — but with hardware, it’s not just about development. You have to ship it, support it, manage logistics, navigate supply chain disruptions, and handle inventory — all while maintaining speed and quality.

How do you see the market for AI-driven safety solutions evolving in the next five or 10 years?

 I believe generative AI will be rapidly adopted in safety applications. Its ability to detect dangerous scenarios that it hasn’t been explicitly trained on is critical—especially since many accidents occur in unpredictable, long-tail situations. The ability to identify and respond to these rare events is essential.

Beyond safety, generative AI is also becoming valuable in video telematics, and operational use cases. For example, it can help determine whether packages were placed correctly or if required inspections were completed. These are areas where generative AI offers real impact.

We recently launched a product that enables natural language video search. Customer interest has been overwhelming, because the use cases are so varied. Every customer seems to discover a different, specific problem they can solve with it. Generative AI enables that flexibility and scale.

“This is where Qualcomm plays a key role in the value chain. Generative AI is extremely compute-intensive, and running it at the edge requires highly efficient, low-power processors. Qualcomm’s advancements in edge AI processing are pushing the boundaries, and their roadmap is very exciting.”

Qualcomm Ventures joined your latest investment round. What factors drove your decision to have Qualcomm Ventures as an investor?

Qualcomm is a pioneer in mobile and edge AI technology, with a strong ecosystem and a bold vision. We see a natural fit in building our application on top of that foundation. That’s why we’re excited to leverage their platform—and we’re grateful that Qualcomm Ventures chose to invest.

What key lessons have you learned as a founder transitioning from a large corporate to a startup, and what advice would you share with others making that leap? 

It really comes down to focus. As a founder, you’re constantly thinking about product, sales, and marketing—while operations often feels like something to worry about later. After all, if you’re not selling anything, operations doesn’t matter. But once you start gaining traction, they absolutely do.

My advice to others: as soon as you see early signs of adoption and success, start planning how you’ll scale your operations. Especially in hardware-centric businesses, operations can quickly become your bottleneck. You might have an incredible product, but without the right operational setup, growth will be limited.

“One of the best pieces of advice I received was from a friend who said, “You’re growing fast, in a massive industry, with limited resources and a lot of constraints. You need to focus on what really matters.”

That stuck with me. I tend to dive deep into the details, but as the business scales, that becomes unsustainable. You have to find the right people, trust them with the details, and shift your attention to the high-impact priorities that will drive the next phase of growth.

What’s that next level for Netradyne?

The total commercial vehicle market in the US alone is about 28 million vehicles. Globally, it’s about three to four times that size. Every company, small and large, has a fleet, and even if they outsource it to a third-party vendor, they’re still responsible for safety. And if you look at the penetration of cameras into that market, it’s less than 10 percent — and AI cameras even less. So there’s a lot of white space, and we’re seeing very, very fast adoption. 

We want to improve our system to reduce accidents even further and reach more of the addressable market. As I see it, the opportunity is just tremendous.