Luminar Technologies

Luminar Technologies R&D per Employee

Delisted

The R&D Spending per Employee of Luminar Technologies (LAZR) as of Oct 31, 2026 is 386,115.00 USD. In the previous year, R&D Spending per Employee was 437,028.33 USD — a change of -11.65% (lower).

R&D per Employee

386,115.00USD

YoY

-11.65%

Last updated:

R&D Spending per Employee of Luminar Technologies is 2024 386,115.00 USD. R&D Spending per Employee of Luminar Technologies was 2023 437,028.33 USD. It decreases by -11.65% lower compared to the previous year.

The Luminar Technologies R&D per Employee history

  • 3 Years

  • 10 Years

  • 25 Years

  • Max

R&D per Employee
Date
R&D per Employee
Jan 1, 2018
66,816.67 USD
Jan 1, 2019
61,616.67 USD
Jan 1, 2020
64,416.67 USD
Jan 1, 2021
148,100.00 USD
Jan 1, 2022
308,800.00 USD
Jan 1, 2023
437,028.33 USD
Jan 1, 2024
386,115.00 USD
The Luminar Technologies R&D per Employee history
YEARR&D per EmployeeYoY
386,115.00USD-11.65%
437,028.33USD+41.52%
308,800.00USD+108.51%
148,100.00USD+129.91%
64,416.67USD+4.54%
61,616.67USD-7.78%
66,816.67USD—

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Luminar Technologies Stock analysis

What does Luminar Technologies do? Luminar Technologies, Inc. generates revenue through its Autonomy Solutions segment, which designs, manufactures, and sells lidar sensors to original equipment manufacturers (OEMs) in the automobile, commercial vehicle, robo-taxi, and adjacent industries. The company also operates an Advanced Technologies and Services (ATS) segment that provides advanced semiconductors, components, design, test, and consulting services to the Autonomy Solutions segment and third-party customers such as government agencies and defense contractors. These services target markets unrelated to autonomous vehicles, including defense and government sectors. The primary buyers are automotive OEMs, robo-taxies, commercial vehicle manufacturers, and government agencies seeking advanced sensor and semiconductor solutions for safety and autonomous capabilities in vehicles and adjacent markets. The firm's product portfolio includes lidar sensors for autonomous driving applications, semiconductors, and related components. These products are sold under the company's brand to OEMs, technology companies, and government agencies. The ATS segment's offerings extend to defense contractors and other third parties, creating a diversified revenue stream across automotive, defense, and technology sectors. Revenue is derived from both direct sales to OEMs and service contracts with government and defense entities. Luminar's business model focuses on high-value sensor technology for autonomous vehicles and adjacent markets, with a dual-segment approach that balances automotive and non-automotive applications. The company's key customers include automotive manufacturers, robo-taxi operators, and government defense contractors, who purchase lidar systems and semiconductor components for integration into their platforms. The ATS segment ensures that the company can monetize its technology beyond the automotive sector, leveraging expertise in semiconductors and design services for broader market applications. Luminar Technologies is one of the most popular companies on Eulerpool.

Frequently Asked Questions about Luminar Technologies stock

R&D Spending per Employee of Luminar Technologies is 386,115.00 USD in 2024.

R&D Spending per Employee of Luminar Technologies changed from 437,028.33 USD to 386,115.00 USD, representing a -11.65% change. The value is lower than the previous year.

On Eulerpool you can find the complete historical development of R&D Spending per Employee Luminar Technologies since 2006 – with annual values, charts, and detailed analysis.

R&D per employee shows the research and development investment allocated per employee. Higher values indicate innovation-focused companies.

R&D Spending per Employee's USD is a key factor for investors. Changes in this metric can signal improving or deteriorating fundamentals, directly impacting the stock price. On Eulerpool, you can track R&D Spending per Employee's Luminar Technologies historically and in real time.

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