TCP Venture Capital

Type

Venture Capital

Status

Active

Location

Hampstead, United States

Total investments

46

Average round size

7M

Portfolio companies

28

Rounds per year

3.83

Lead investments

8

Follow on index

0.39

Exits

2

Stages of investment
Early Stage Venture
Areas of investment
E-CommerceInternetSoftwareAnalyticsInformation TechnologyHealth CareSaaSEducationMedicalCompliance

Summary

TCP Venture Capital appeared to be the VC, which was created in 2012. 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 Hampstead.

The standard case for the fund is to invest in rounds with 4-5 partakers. Despite the TCP Venture Capital, startups are often financed by TEDCO, Frank A. Bonsal, Jr., Dingman Center for Entrepreneurship. The meaningful sponsors for the fund in investment in the same round are Baltimore Angels, TEDCO, Maryland Venture Fund. In the next rounds fund is usually obtained by LionBird, Kaiser Permanente Ventures, F-Prime Capital.

The current fund was established by Christopher College, Stuart Sutley.

Speaking about the real fund results, this VC is 7 percentage points less often commits exit comparing to other organizations. Deals in the range of 5 - 10 millions dollars are the general things for fund. Comparing to the other companies, this TCP Venture Capital performs on 20 percentage points less the average number of lead investments. The increased amount of exits for fund were in 2017. The fund is constantly included in 2-6 investment rounds annually. The top activity for fund was in 2015. Despite it in 2019 the fund had an activity.

Among the most popular portfolio startups of the fund, we may highlight Pixelligent, ZeroFOX, Insightin Health. The fund has no exact preference in a number of founders of portfolio startups. We can highlight the next thriving fund investment areas, such as Analytics, Medical. For fund there is a match between the location of its establishment and the land of its numerous investments - United States. Besides, a startup needs to be aged 4-5 years to get the investment from the fund.

Show more

Investor highlights

Industry generalist
Yes
Industry focus
GeneralistAI/Big DataB2B/EnterpriseCloud/InfrastructureConsumer/Retail Show 6 more
Stage focus
Series ASeries B
Geo focus
United States, Maryland, Baltimore

Discover reliable insights

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

Investments analytics

Analytics

Total investments
46
Lead investments
8
Exits
2
Rounds per year
3.83
Follow on index
0.39
Investments by industry
  • Software (26)
  • Information Technology (13)
  • Health Care (10)
  • Analytics (9)
  • Internet (8)
  • Show 59 more
Investments by region
  • United States (46)
Peak activity year
2014
Number of Unicorns
1
Number of Decacorns
1

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
9
Avg. valuation at time of investment
67M
Group Appearance index
0.67
Avg. company exit year
6
Strategy success index
0.10

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
Bioforany 05 May 2023 Biotechnology, Manufacturing, Medical, Chemical Seed Jiangsu, Changsha, China
EcoMap Technologies 14 Aug 2023 Software, Analytics, Communities, Business Intelligence Seed 3M United States, Maryland, Baltimore
Traitify 08 Jul 2014 Software, Human Resources, Recruiting, SaaS, Career Planning, Personalization, Developer APIs, Employment, Skill Assessment Early Stage Venture 4M United States, Maryland, Baltimore

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.