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Netradyne Tech Stack

AI-powered fleet safety platform using computer vision and edge computing

Software Development San Diego, California 501–1,000 employees Founded 2015 Privately Held
netradyne.com LinkedIn

Netradyne builds fleet safety systems using computer vision and edge computing to monitor driver behavior and vehicle performance in real time. The tech stack reveals a security-heavy organization—Burp Suite, Metasploit, Nessus, Kali Linux, Qualys, Wazuh, Sentinel across the toolchain—combined with aggressive adoption of GPU/CUDA/OpenCL, signaling both mature infosec practices and intensive ML inference at the edge. Hiring velocity is accelerating with 46 roles posted in the last 30 days, heavily weighted toward senior engineering and staff-level talent, reflecting pressure to scale driver monitoring algorithms and modernize legacy platform infrastructure.

Tech Stack 132 technologies

Core StackPostgreSQL MySQL ServiceNow Jira Salesforce SonarQube Splunk AWS Apex Python Java JavaScript Burp Suite Metasploit Nessus Nmap Kali Linux Qualys Sentinel Wazuh Azure Android iOS Salesforce Lightning Salesforce CPQ Salesforce Marketing Cloud Salesforce Community Cloud Salesforce Service Cloud Salesforce Sales Cloud Bash+100 more
AdoptingGPU CUDA OpenCL SNPE

What Netradyne Is Building

◆Challenges

  • Preventing accidents in real-time
  • Expanding international market
  • Maintaining high-quality crm data
  • Modernizing legacy enterprise applications
  • Scaling business-critical platforms
  • Improving developer productivity
  • Shortening sales cycles
  • Increasing win rates
  • Customer issue resolution
  • Mitigating cyber threats

▲Active Projects

  • Driver monitoring and driver assistance algorithms
  • Cots device validation
  • International product launch execution
  • Product test plans (ptp) across product lifecycles
  • Digital platform modernization
  • Business-critical platform delivery
  • Vertical go-to-market strategy
  • Product launch strategy
  • Integrated multi-channel campaigns
  • Webinar program

Hiring Activity

Accelerating55 roles · 45 in 30d

Department

Engineering
24
Data
6
Sales
6
Finance
4
Marketing
3
Ops
3
Support
3
Security
2

Seniority

Senior
24
Staff
14
Junior
4
Director
3
Lead
3
Mid
3
Manager
2
Principal
1

Notable leadership hires: Test Lead

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About Netradyne

Netradyne operates a fleet safety platform for commercial transportation companies. The product ingests video and telemetry from vehicle-mounted edge devices, processes driver behavior and vehicle diagnostics through computer vision models, and surfaces actionable insights via a cloud-based dashboard. The company collects and analyzes fleet data to help operators improve driver retention, increase profitability, and enhance safety standards. Netradyne serves mid-market and enterprise transportation operators and is expanding internationally; the organization is 501–1,000 employees, headquartered in San Diego, and was founded in 2015.

HeadquartersSan Diego, California
Company Size501–1,000 employees
Founded2015
Hiring MarketsUnited States, India

Frequently Asked Questions

What tech stack does Netradyne use?

PostgreSQL, MySQL, AWS, Azure, Salesforce (Sales Cloud, Service Cloud, CPQ, Marketing Cloud), ServiceNow, Jira, Splunk, Sentinel, Wazuh, and security tools including Burp Suite, Metasploit, Nessus, Qualys. Currently adopting GPU, CUDA, OpenCL, and SNPE for edge inference.

What is Netradyne working on?

Driver monitoring and driver assistance algorithms, product test plans across lifecycle, digital platform modernization, business-critical platform scaling, international product launch execution, vertical go-to-market strategy, and integrated multi-channel demand campaigns.

How this profile is built

Netradyne's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.