SAIC Capital

Type

CVC

Status

Active

Location

Menlo Park, United States

Total investments

51

Average round size

20M

Portfolio companies

43

Rounds per year

2.12

Lead investments

5

Follow on index

0.16

Exits

15

Stages of investment
Early Stage VentureLate Stage Venture
Areas of investment
AutomotiveLogisticsTransportationSoftwareInformation TechnologyArtificial IntelligenceManufacturingAutonomous VehiclesSemiconductorTelecommunications

Summary

SAIC Venture Capital is the famous VC, which was founded in 2000. The venture was found in North America in United States. SAIC Venture Capital appeared to be a CVC structure as part of the corporation. The main department of described VC is located in the Las Vegas.

Besides them, we counted 5 critical employees of this fund in our database.

Besides, a startup requires to be at the age of 4-5 years to receive the investment from the fund. Among the most popular fund investment industries, there are Artificial Intelligence, Telecommunications. Among the most popular portfolio startups of the fund, we may highlight Solect Technology Group, Banma Network Technologies, Plus.ai. The fund has specific favorite in a number of founders of portfolio startups. If startup sums 5+ of the founder, the chance for it to be financed is low. For fund there is a match between the country of its foundation and the country of its the most frequent investments - United States.

The typical case for the fund is to invest in rounds with 5-6 participants. Despite the SAIC Venture Capital, startups are often financed by Intel Capital, Alpine Electronics, H.I.G. Capital. The meaningful sponsors for the fund in investment in the same round are Intel Capital, TSVC, Sony Innovation Fund. In the next rounds fund is usually obtained by General Motors Ventures, Motus Ventures, Cordova Ventures.

The fund is constantly included in less than 2 deals per year. The usual things for fund are deals in the range of 10 - 50 millions dollars. Speaking about the real fund results, this VC is 5 percentage points less often commits exit comparing to other organizations. The typical startup value when the investment from SAIC Venture Capital is 100-500 millions dollars. The higher amount of exits for fund were in 2016. Opposing the other organizations, this SAIC Venture Capital works on 3 percentage points more the average amount of lead investments. The important activity for fund was in 2000. Despite it in 2019 the fund had an activity.

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Investor highlights

Industry focus
Climate techDeep TechMobilityIoTAI/Big Data Show 4 more
Stage focus
Series DSeries ASeries ESeries FSeries B Show 1 more
Geo focus
Generalist
Check size
1M — 20M

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Investments analytics

Analytics

Total investments
51
Lead investments
5
Exits
15
Rounds per year
2.12
Follow on index
0.16
Investments by industry
  • Software (21)
  • Automotive (12)
  • Manufacturing (10)
  • Artificial Intelligence (10)
  • Logistics (7)
  • Show 73 more
Investments by region
  • United States (34)
  • China (10)
  • United Kingdom (3)
  • Canada (2)
  • Malaysia (1)
  • Show 1 more
Peak activity year
2018
Number of Unicorns
3
Number of Decacorns
4
Number of Minotaurs
1

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Quantitative data

Avg. startup age at the time of investment
17
Avg. valuation at time of investment
752M
Group Appearance index
0.88
Avg. company exit year
12
Avg. multiplicator
15.32
Strategy success index
0.80

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Actional Garners 30 Jan 2002 Software, Computer, Web Development Late Stage Venture 26M United States, California, Mountain View
Extreme Vision 05 May 2016 Information Technology, Machine Learning, Cloud Data Services, Computer Vision Seed Hunan, China, China
Quincus 16 Nov 2021 Logistics, Transportation Early Stage Venture Central, Singapore, Singapore

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How we get our data

At Unicorn Nest, we combine cutting-edge technology with human expertise to build one of the most reliable venture capital databases in the market. Our process begins with automated AI-enhanced data collection, leveraging the full potential of Large Language Models (LLMs).

Later, our team of analysts takes it further with manual verification, using proprietary tools for data cleaning and validation to ensure accuracy and reliability. We cross-check and enhance our findings through press and media monitoring, integrating information from trusted news outlets and venture capital aggregators. Finally, we stay ahead of the curve by monitoring social networks like LinkedIn and X.com.