Houston Angel Network

Type

Non-Profit

Status

Active

Location

Houston, United States

Total investments

183

Average round size

867K

Portfolio companies

116

Rounds per year

7.96

Lead investments

6

Follow on index

0.37

Exits

16

Stages of investment
Seed
Areas of investment
BiotechnologySoftwareInformation TechnologyFood and BeverageHealth CareManufacturingMedical DeviceMedicalEnergyOil and Gas

Summary

Houston Angel Network is the famous VC, which was founded in 2001. The fund was located in North America if to be more exact in United States. The main office of represented VC is situated in the Houston.

The overall number of key employees were 4.

The increased amount of exits for fund were in 2018. The common things for fund are deals in the range of 100 thousands - 1 million dollars. Comparing to the other companies, this Houston Angel Network performs on 20 percentage points less the average number of lead investments. The typical startup value when the investment from Houston Angel Network is 5-10 millions dollars. The high activity for fund was in 2014. Despite it in 2019 the fund had an activity. The fund is constantly included in 7-12 investment rounds annually. Considering the real fund results, this VC is 13 percentage points less often commits exit comparing to other organizations.

The typical case for the fund is to invest in rounds with 1-2 participants. Despite the Houston Angel Network, startups are often financed by Mercury Fund, Texas Halo Fund, S3 Ventures. The meaningful sponsors for the fund in investment in the same round are Mercury Fund, Tech Coast Angels, Tekton Ventures. In the next rounds fund is usually obtained by S3 Ventures, SURGE Accelerator, HealthpointCapital.

Among the most popular portfolio startups of the fund, we may highlight Onit, Procyrion, Optical Entertainment Network. For fund there is a match between the country of its foundation and the country of its the most frequent investments - United States. The fund has no exact preference in a number of founders of portfolio startups. If startup sums 5+ of the founder, the chance for it to be financed is low. Moreover, a startup needs to be at the age of 2-3 years to get the investment from the fund. Among the most popular fund investment industries, there are Information Technology, Food and Beverage.

Show more

Investor highlights

Discover reliable insights

Find relevant VC investors, identify key contacts and secure funding opportunities.

Investments analytics

Analytics

Total investments
183
Lead investments
6
Exits
16
Rounds per year
7.96
Follow on index
0.37
Investments by industry
  • Health Care (42)
  • Software (37)
  • Manufacturing (35)
  • Medical (33)
  • Information Technology (25)
  • Show 138 more
Investments by region
  • United States (172)
  • Canada (3)
  • Romania (2)
  • United Kingdom (2)
  • France (1)
Peak activity year
2014

Discover reliable insights

Leverage validated data, identify key contacts and secure funding opportunities for your business.

Quantitative data

Avg. startup age at the time of investment
13
Avg. valuation at time of investment
4M
Group Appearance index
0.33
Avg. company exit year
7
Avg. multiplicator
4.59

Need more data?

Get access to full data about investors, including their team, contact information, and historic data.

Latest deals

Company name Deal date Industry Deal stage Deal size Location
Autonomous Marine Systems 13 Mar 2014 Robotics, National Security, Marine Technology Seed 105K United States, Massachusetts
Materna Medical 21 May 2024 Health Care, Medical Device, Medical Early Stage Venture 5M United States, California, Mountain View
SpyCloud 01 Jun 2017 Cyber Security, Network Security, Security, Fraud Detection Seed 2M United States, Texas, Austin

Similar funds

By same location

By same geo focus

By doing lead investments

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.