Raven Connected and Swift Navigation Partner to Launch AI-Driven Spatial Intelligence for More Responsive Infrastructure Management

Strategic collaboration combines AI vision with centimeter-accurate GPS to automate infrastructure inspection and create real-time “Digital Twins” of road networks.

LAS VEGAS – January 5, 2026 – Raven Connected, the end-to-end AI video telematics and intelligent transportation systems (ITS) platform, and Swift Navigation, a pioneer in precise positioning technology for mass market applications, today announced a strategic partnership to deliver Spatial Intelligence at scale. By integrating Swift’s Skylark™ Precise Positioning Service with Raven’s edge-computing AI, the collaboration enables municipalities and fleet operators to automatically detect, map, and manage road assets with lane-level accuracy.

The Problem: The Record-High Cost of the “Data Gap”

For municipalities and Departments of Transportation, maintaining road networks is a battle against stale data. Traditional asset management relies on manual, infrequent surveys or standard GPS tracking, which often has a margin of error of several meters.

In complex urban environments, this lack of precision creates a costly “Data Gap.” Road managers cannot distinguish between lanes, pinpoint specific infrastructure defects (like potholes or damaged signage) with certainty, or efficiently deploy repair crews. This results in reactive maintenance, wasted budget on manual verification, and increased safety risks for the public.

The Solution: Crowdsourced Precision and Spatial Intelligence

Raven and Swift are closing this gap by transforming everyday service vehicles into high-precision, always-on mapping sensors. By embedding Swift’s Skylark into Raven’s AI OBUs (Onboard Units), the platform captures live road video and converts it into structured, centimeter-accurate geospatial data.

This integration delivers a “Ground Source Truth” solution that empowers public works teams to:

  • Automate Asset Mapping: Eliminate the need for dedicated survey vehicles by automatically detecting and geocoding signage, lane markings, and road defects during regular operations.
  • Achieve Lane-Level Precision: Utilize Swift’s corrections to achieve lane–level accuracy, essential for distinguishing hazards in specific lanes or dense urban canyons.
  • Streamline Maintenance: replace manual data entry with a real-time digital twin of the road network, allowing for proactive repairs and accurate work-order generation.

The Future: Powering the Autonomous Ecosystem

Beyond immediate municipal and fleet applications, the partnership addresses the critical demand for fresh, high-definition (HD) map data in the autonomous vehicle industry. Standard maps cannot keep pace with changing road dynamics; however, the continuous stream of anonymized, high fidelity data collected by Raven-equipped fleets creates a ‘Living Map.’ This provides the AV industry with a scalable, self-healing data layer that is vital for the safe operation and validation of autonomous systems

“Our philosophy is about providing the most accurate, actionable intelligence possible,” said Dan Carruthers, CEO of Raven Connected. “By embedding Swift’s precise GNSS technology, we ensure our partners aren’t just getting data, they are getting ‘Ground Source Truth.’ This level of precision is the key to unlocking new business opportunities, from automated infrastructure inspection to supporting the global shift toward autonomy.”

“The evolution of AI and machine learning requires a live, virtual replica of the world,” added Holger Ippach, EVP of Product & Marketing at Swift Navigation. “When you combine Raven’s edge-computing power with Swift’s absolute precision, you empower fleets to make smarter, data-driven decisions that impact the bottom line immediately.”

Experience the Future at CES 2026

Swift Navigation will showcase this integrated solution at CES 2026 in the LVCC West Hall, Booth #3155. Attendees can see firsthand how the fusion of video telematics and precise positioning is redefining the connected vehicle ecosystem.

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