At a glance: Bot Auto is redefining what’s possible in commercial trucking autonomy. With an elite team of around 80 people, including 50 engineers, Bot Auto is competing on a technical benchmark that typically demands organizations ten times their size. Their advantage isn’t headcount. It’s architecture. By building on best-in-class platforms from day one, Bot Auto moves with the velocity of a startup and the technical credibility of a Tier 1.
Why You Can't Automate What You Can't Locate
Every autonomous vehicle has to solve a positioning problem before anything else can work. A truck that doesn’t know exactly where it is, to the centimeter, can’t make the split-second decisions that autonomy demands. It can’t stay in its lane at highway speed. It can’t execute a precise dock approach. It can’t earn the certifications that unlock commercial deployment.
For many AV teams, this is the invisible bottleneck. Sensor fusion, perception, path planning, these get the attention. GNSS gets overlooked. Teams assume their existing GPS receiver is good enough, not realizing that standard GPS carries meters of error that compound across every downstream system. By the time they understand what they’re missing, they’ve lost months and burned significant engineering resources.
Bot Auto didn’t make that mistake.
Bot Auto’s Location Stack
Bot Auto runs on purpose-built compute for real-time perception, planning, and control. Their AI models are trained and validated on leading simulation infrastructure, giving their lean engineering team access to the same tools that power the industry’s most sophisticated AV programs. Bot Auto already operates its own upfitted vehicles, running a fleet that reflects both the depth of the integration and their trajectory toward scaled commercial deployment. Point One provides the centimeter-accurate positioning layer.
Bot Auto’s vehicles carry standard GNSS receivers, the same hardware already on most outdoor devices. What Point One adds is its RTK (Real-Time Kinematic) correction service. The combination is straightforward in concept and transformative in practice: the GNSS receiver captures raw satellite signals; Point One’s RTK engine delivers real-time atmospheric corrections that collapse positioning error from 5+ meters to 1–3 centimeters, a 100x improvement in location accuracy.
The integration point is the vehicle’s onboard compute stack. Point One’s RTK engine is designed to run directly on the vehicle’s existing compute hardware, the same platform processing perception and planning is also processing positioning corrections. This isn’t a bolt-on. It’s a unified architecture where precise location data flows directly into the autonomy stack at the speed the system requires. Just as Point One has enabled RTK processing directly on the compute hardware of leading electric vehicle manufacturers, Bot Auto benefits from the same approach: corrections computed on-platform, with no latency introduced by external hardware dependencies.
Point One’s RTK correction service is designed to run natively on the vehicle’s existing compute hardware, which means precise positioning data flows directly into the autonomy stack without external dependencies. For teams like Bot Auto operating at commercial scale, that kind of architecture makes a real difference.
Positioning Accuracy Is a Certification Problem, Not Just a Performance Problem
For commercial AV deployment, certification is everything. Regulators, fleet operators, and insurance underwriters all want demonstrated, repeatable, verifiable performance. “Works most of the time” is not a standard anyone certifies against.
This is where the physics of GNSS correction becomes a business issue.
Atmospheric conditions, ionospheric disturbances, tropospheric variation driven by weather and water vapor, introduce localized, unpredictable errors into GNSS signals. These errors don’t follow a smooth curve. They spike. And when they spike, standard GPS drifts. A system that reports 50 cm accuracy at the median can produce 3–5 meter errors at the tail.
Point One’s RTK corrections network is built specifically to prevent this. With 40 km average station spacing, nearly three times denser than typical commercial networks, Point One provides samples of corrected atmospheric conditions at fine enough resolution to capture localized disturbances before they propagate into positioning error. The result isn’t just better average accuracy. It’s tighter tails. Fewer excursions. A distribution of positioning performance that a certification team can actually evaluate and trust.
For Bot Auto, this means the positioning data feeding their autonomy stack isn’t just accurate in nominal conditions. It’s accurate in the conditions that matter most: adverse weather, high-traffic corridors, challenging signal environments. The 99th percentile performance is what earns commercial contracts. Point One is what makes that performance achievable.
Doing More with Less
Bot Auto’s team size is a feature, not a limitation, but only because every architectural choice multiplies their leverage. Integrating Point One’s RTK service meant no custom GNSS infrastructure to build, no atmospheric modeling to develop, no reference network to deploy and maintain. They inherited the densest professionally-managed GNSS reference network in the world on Day One.
The engineering hours that would have gone into positioning infrastructure went into autonomy and navigation instead. And the positioning performance they achieved is better than what most teams build with dedicated resources, because Point One’s network reflects years of infrastructure investment that no AV startup would replicate from scratch.
The same logic applies to positioning infrastructure. By integrating Point One’s RTK correction service directly into the autonomy stack, Bot Auto gets centimeter-accurate positioning without building or maintaining a corrections network from scratch. Point One for positioning lets a team of 50 engineers compete on a technical benchmark built for organizations of 2,000 or more.
What Comes Next
Bot Auto is on the path to commercial deployment in autonomous trucking, a market where precision, reliability, and regulatory trust aren’t differentiators. They’re entry requirements. As Bot Auto’s deployment scales, Point One’s RTK engine scales with it, same hardware, same platform, international range, higher confidence.
The future of autonomous trucking isn’t being built by the largest teams. It’s being built by the most architecturally disciplined ones. Bot Auto is proof of that, and the autonomy stack they’ve assembled with Point One reflects it at every layer.
Building autonomous systems that need precision location? Point One’s RTK network delivers centimeter-level accuracy with network redundancy built in. No base stations. No single points of failure. Just reliable positioning that scales with your deployment.