Market research
GTLB Gitlab Inc
NASDAQ USD Technology
Latest close
As of 30 Oct 2026
Test a moving-average rule with historical data.
Market facts
- Market cap
- 9B
- P/E ratio
- Not available
- Analyst target
- 56.125
- Dividend yield
- Not available
- Beta
- 0.99
Profile
Instrument facts
- Exchange
- NASDAQ
- Currency
- USD
- Sector
- Technology
- Industry
- Software - Infrastructure
- ISIN
- Not available
- Market cap
- 9B
- P/E ratio
- Not available
- Analyst target
- 56.125
- Dividend yield
- Not available
- Beta
- 0.99
About
About Gitlab Inc
GitLab Inc., together with its subsidiaries, develops software for the software development lifecycle in the United States, Europe, and the Asia Pacific. The company provides GitLab, an intelligent orchestration platform for DevSecOps, which is a single application offering the entire software development lifecycle, including software, project plans, code, security scans, compliance checks, and deployment configurations. It also offers the GitLab Duo Agent Platform, which enables intelligent orchestration of teams and AI agents to execute tasks autonomously across planning, development, security, and deployment. This platform combines conversational AI assistance, purpose-built agents for specialized tasks, workflow automation, and enterprise controls. In addition, it offers related training and professional services. The company was formerly known as GitLab B.V. and changed its name to GitLab Inc. in July 2015. GitLab Inc. was founded in 2011 and is based in San Francisco, California.
Research context
Gitlab Inc appears in PyInvesting’s US Stock catalogue. The price history above describes this recorded instrument; it does not by itself identify a company’s business or establish a continuous investment return.
- Currency
- USD
- Sector
- Technology
- Industry
- Software - Infrastructure
These are the latest stored catalogue classifications, not a historical classification snapshot. An issuer description, classification effective date or currency may be unavailable. Check the issuer’s own disclosures and the observation dates before using these fields for research.
Review backtest assumptions and evidence before treating a chart or stored history as a research result.
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