AI-powered investment marketplace

AI-powered marketplace matching investors with startups, achieved a 32% accuracy improvement in predicting investment success, and a 25% reduction in investment risks.

Client

A California-based startup in the VC investment industry.

Objective

Our client spent over a year analyzing profiles of a wide range of startups to see if there is a way to predict the success of a given company before pouring money into it. It turned out that data analytics alone was not able to produce accurate results. So they set their eyes on the emerging field of Artificial Intelligence to get more help.

After investing a significant amount of time and energy, they came up with a proprietary AI-based approach that yielded much better outcomes. Now they needed a company who could turn their mathematical algorithms into a product.

Solution

Using recurrent neural network framework as the brain of the solution, we turned the client’s mathematical algorithms into an elegant AI based product.

Features include:

Consumption of multiple data points about a given startup organization and prediction data set generation
A backend services layer that ingests the data and serves it to a slick user interface
A user interface that presents the outcome in easy to read graphs and charts

Result

The proprietary AI-based approach to predicting the success of investments yielded much better outcomes than data analytics alone. The AI based product makes it easy for the end-user to make business decisions for various investment scenarios.

Improved accuracy: achieved an increase of 32% in the accuracy of investment success predictions compared to traditional data analytics.
Risk Reduction: showcased a 25% reduction in investment risks, contributing to enhanced overall reliability in decision-making processes.
Enhanced Data Analysis: the recurrent neural network framework facilitated the consumption of diverse data points, leading to increase in the granularity of startup organization analysis.
Precise Forecasting: prediction dataset generation exhibited enhancement in accuracy, providing more precise forecasts for various investment scenarios.