While running pre-screens on TeQatlas’s platform, investors can see the company's relevancy within seconds. This became possible for investors with the Fit Rate (recently known as Relevance Score) designed to qualify the companies by relevance to the investment focus easily.
TeQatlas aims to assist investors in selectively targeting relevant startups to increase the quality of their deal flow of private companies by accelerating their workflow and fastening the time to insights.
TeQatlas’s Fit Rate helps investors qualify and prioritize the most relevant companies out of the hundreds in their deal flow. This proprietary score was designed to surface the most relevant companies and help you reach them at the right time.
The investors visit companies' websites (startups) to find out what they do and whether they fit their investment focus. An investor must not spend hours manually screening startups because TeQatlas Extension provides a Fit Rate for each company (startup) in the TeQatlas database in seconds. The extension has functionality that redirects the investor user to the platform, where the Intelligent Personal Assistant called Toshi notifies the investor about new messages in the Chat Room on the platform.
The company receives a Fit Rate between 0 and 100, with 100 being the highest.
The algorithm calculates the relevance of a startup IN SECONDS from the extensive company dataset.
There are 1+ mln companies under the hood and counting.
Neural networks accurately define companies’ industries.
Insight generation happens under the hood based on investment preferences and data on the startup landscape. The system design makes it possible to start using TeQatlas in one click, applying advanced technologies, computational analytics techniques, and scientific approaches to find pairs of only relevant investees and investors.
A massive amount of (un)structured data on the global private market needs to be stored and interpreted, identifying correlations and patterns to predict new trends and needs across diverse markets.
In the absence of similar solutions on the market, the TeQatlas team has hand-crafted potential indicators of investor preferences, incorporating our knowledge of the capital-raising market.
We rely heavily on data mining, machine learning, and neural networks to quickly analyze these data with accuracy and reliability. Thus investors can save time, simplify decision-making, and get things done.
