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Netradyne Unveils Real-Time, Natural-Language Search for In-Cab Video

Netradyne says its Video LiveSearch enables real-time, natural-language search of in-cab video, allowing fleets to instantly surface the most meaningful footage for safety, coaching, and operations.

Netradyne Unveils Real-Time, Natural-Language Search for In-Cab Video

Netradyne's new Video LiveSearch lets fleet managers instantly find relevant in-cab video across the fleet, without waiting on cloud processing or manual downloads.

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Netradyne

3 min to read


Netradyne said its new Video LiveSearch enables real-time natural-language search of its in-cab video, allowing fleet managers to search across every vehicle and instantly uncover the most meaningful video to pull.

Until now, according to Netradyne, fleets had to rely on incidents being reported by other teams, wait through cloud processing delays, manually triangulate the vehicle and timeframes of interest to download, and then sift through hours of downloaded footage.

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Video LiveSearch enables fleets to shift from a reactive to a proactive operational approach:

  • Teams can proactively improve safety and performance with nearly instant line-of-sight into where to look, instead of waiting for reports or digging through timelines.

  • The real-time, on-device search uses a simple, natural-language prompt for road-facing camera views across the entire fleet.

  • It helps fleet managers find the most relevant before-, during-, and after-video clips, instead of guessing or manually triangulating video timestamps.

“Video LiveSearch is the fleet industry’s first on-device, real-time search capability,” said Avneesh Agrawal, CEO and co-founder of Netradyne, in a news release.

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Powered by On-Device Edge AI

Video LiveSearch is possible because of Netradyne’s advanced edge artificial intelligence.

Real-Time Reasoning at the Edge

Netradyne creates searchable video for virtually 100% of road-facing drive time directly on the vehicle. Video LiveSearch doesn’t have to wait on cloud downloads to start finding relevant video.

Every free-text search returns top matches in seconds, whether across a single vehicle or the entire fleet. Instead of chasing details like vehicle, date, or trip and hoping a video request hits the mark, fleet managers can immediately see the best matches and download only the footage they need.

Context-Aware Search that Learns Real-World Patterns

Netradyne’s edge intelligence learns patterns in real-world road scenes and driving behavior, enabling LiveSearch to instantly match a simple search prompt to the most relevant video footage and return the right clips to pull for before, during, and after context.

Two-Speed AI: Discover Fast, Operationalize with Precision

Netradyne views Video LiveSearch as a core pillar of its two-speed artificial intelligence strategy.

Exploration: Broad semantic search enables rapid discovery without waiting on product development cycles.

Operationalization: High-precision, domain-optimized models power real-time coaching and safety-critical workflows.

“The enabling hardware for Video LiveSearch, the D-810 device, turns every vehicle into an intelligent multi-modal sensor for your fleet operations,” said David Julian, CTO and co-founder of Netradyne. 

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“Video LiveSearch leverages that intelligence to deliver rapid insights, giving fleets the power to quickly search for what’s happening around their vehicles, drivers, and passengers in real time.

“This represents a foundational step in our Physical AI platform, where our technology continuously interprets the physical world to power both rapid discovery and precision operations."

Responsible AI by Design

Video LiveSearch embeds responsible AI governance directly into its architecture. 

An AI front-end screening layer evaluates natural-language prompts before they reach the edge reasoning engine, automatically rejecting requests outside approved operational intent — such as identifying individuals or tracking license plates.

This approach ensures Video LiveSearch remains focused on safety and operational use cases, preserves driver trust, and prevents misuse by design rather than policy.

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