DORIOT AI LTD

Meet DORIOT AI LTD.

Doriot uses cutting-edge machine learning algorithms to match startups with the right investors, including Business Angels and Venture Capital firms. By streamlining this process, Doriot saves founding teams valuable time and addresses inefficiencies in the startup investment ecosystem, ensuring startups are paired with investors who align with their industry, growth stage, and strategic goals.

Doriot logo

The Team

Zain Aamir 

Sartaj Syed 

Filippo Menolascina 

About Us

Filippo Menolascina is a MIT-trained academic with a 20-year track record of research in Artificial Intelligence, MBA-level education, executive and VC investment experience. A serial entrepreneur, Filippo leverages 10+ years of Board-level experience in early stage ventures to advise investors and startups on science, strategy and finance.

Sartaj Syed is a computer science graduate from the University of Edinburgh, with additional previous credentials including a PG Diploma from IIIT-D and a Bachelor's degree in EEE from Osmania University. With over 3 years of software development experience at major tech firms, Sartaj has a robust background in AI and IoT research. An AI enthusiast, he is dedicated to driving efficiency and solving complex problems through data and technology.

Zain Aamir is an accomplished Data Scientist & Business Analyst with two years of expertise in Age-Tech, strategic financial modeling, and business analysis. With a Master of Science in Data Science from the University of Edinburgh, Zain combines a strong academic foundation with practical experience in both research and industry. As a Business Analyst, Zain spearheaded the creation of an incubator process for startups, driving innovation in Age-Tech. Previous roles at Toulouse School of Economics and Erasmus School of Law involved leading complex experimental studies and optimizing data management.

Problem

Doriot addresses inefficiencies in the startup investment ecosystem by matching early-stage startups with the right investors. Traditional networking methods and manual research often lead to missed opportunities and suboptimal matches. Startups face challenges in identifying promising investors due to vast data and outdated networks. Using advanced machine learning, Doriot analyzes key factors like industry, stage, and strategic fit, providing precise, personalized matches that save time and improve outcomes for both startups and investors.

Solution

Doriot uses state-of-the-art machine learning algorithms to efficiently match early-stage startups with the right investors and Venture Capital firms. By analyzing factors like industry, stage, and strategic fit, Doriot streamlines the traditionally time-consuming process of connecting startups and investors. This solution saves founding teams hundreds of hours and addresses inefficiencies in the private capital markets, ensuring more precise, effective matches that foster growth and innovation.

Market

Doriot targets early-stage startups in the UK, irrespective of industry, with a phased go-to-market strategy. Beginning with a pilot phase, we validate and refine our platform. Our Ideal Customer Profile includes early-stage startups primarily pre-revenue or with minimal revenue. In the short term, we partner with university accelerators like Edinburgh and Oxford, gather user feedback, engage early adopters, and offer trials with free investor matches. Long-term scaling involves enhancing VC partnerships, comprehensive marketing, event participation, and social media engagement. This ensures robust market penetration, establishing Doriot as an essential tool for startups and investors.