Opendata, web and dolomites


Intelligent investment analysis of early-stage companies

Total Cost €


EC-Contrib. €






Project "INTEL-1" data sheet

The following table provides information about the project.


Organization address
address: 20-22 WENLOCK ROAD
city: LONDON
postcode: N17GU
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2015
 Funding Scheme SME-1
 Starting year 2016
 Duration (year-month-day) from 2016-03-01   to  2016-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CROWD ANALYTICS LTD UK (LONDON) coordinator 50˙000.00


 Project objective

The European startup ecosystem is booming. It has attracted more than $3.5bn of venture funding in Q3 2015, the highest in 5 years. A major factor fueling this growth is a higher-resolution venture finance industry, which has opened up the traditional Venture Capital (VC) space to new types of early-stage investors: angels, crowdfunding networks, accelerators and micro-VCs.

The challenge these early-stage investors face is the lack of commercially available business intelligence tools to support the decision-making process. The high-risk nature of early-stage investing increases the odds of mis-allocating capital and is raising concerns from industry professionals and regulators alike.

Crowd Analytics is a first-of-its-kind large-scale data analytics and visualisation platform that helps investors assess the risk profile and investment-readiness of early-stage companies. The system collects structured and unstructured data from a number of public and private sources, correlates them using proprietary algorithmic analysis, deduces relevant insights and presents them to the user in an intuitive and structured manner.

This results in reliable, data-driven insights across the complete spectrum of early-stage investment opportunities that will be offered through a subscription service.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "INTEL-1" project.

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The information about "INTEL-1" are provided by the European Opendata Portal: CORDIS opendata.

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