Market research
ALAB Astera Labs, Inc.
NASDAQ USD Technology
Latest close
As of 29 Oct 2026
Test a moving-average rule with historical data.
Market facts
- Market cap
- 45B
- P/E ratio
- 126.59
- Analyst target
- 382.6778
- Dividend yield
- Not available
- Beta
- 3.69
Profile
Instrument facts
- Exchange
- NASDAQ
- Currency
- USD
- Sector
- Technology
- Industry
- Semiconductors
- ISIN
- Not available
- Market cap
- 45B
- P/E ratio
- 126.59
- Analyst target
- 382.6778
- Dividend yield
- Not available
- Beta
- 3.69
About
About Astera Labs, Inc.
Astera Labs, Inc. designs, manufactures, and sells semiconductor-based connectivity solutions for cloud and AI infrastructure in Taiwan and the United States. It offers an intelligent connectivity platform, comprised of semiconductor-based, high-speed, mixed-signal connectivity products that integrate a matrix of microcontrollers and sensors, and COSMOS. The company provides COSMOS software suite, a connectivity system management and optimization software that enables management and optimization of resources for large fleets at cloud-scale via link, fleet, and RAS management capabilities. In addition, it offers PCIe/CXL smart DSP retimers and cable modules; ethernet smart cable modules for cloud and AI infrastructure; CXL memory connectivity controllers; and smart fabric switches. The company serves hyperscalers and system original equipment manufacturers. Astera Labs, Inc. was incorporated in 2017 and is based in San Jose, California.
Research context
Astera Labs, 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
- Semiconductors
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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