Deal Recommendation Engine

Objective

Liquidity Digital, a key digital player in private equity and capital markets, sought to revolutionize their investment brokering process. They needed an AI-powered solution to intelligently match venture capitalists (VCs) with startups, streamlining the deal-making process.

What We've Done

Our team embarked on a transformative journey to deliver a powerful deal recommendation engine. This solution harnessed the potential of custom k-nearest-neighbor (kNN) algorithms and web scraping techniques to redefine how deals are initiated in the industry.

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Design Process

1. Comprehensive Data Gathering

We meticulously gathered data from diverse sources, including company websites, LinkedIn, and Gust, through a multi-functional web scraper built with Selenium and Beautiful Soup (BS4). This data formed the bedrock of our recommendation system with over 10k startups sourced for their network of investors.

2. Custom kNN Algorithm with Intelligent Matching

Our custom kNN algorithm factored in various investor preferences, such as startup stage, industry, annual revenue, location, and more. This ensured highly relevant matches between VCs and startups, with a given "match score" depending on the algorithms output based on these metrics.

3. Full-Stack Development

To create a robust MVP (Minimum Viable Product), we extended our capabilities to more full-stack development:

- Database Design: We designed a scalable and efficient database architecture with posgreSQL to store and manage the vast amount of data generated and used by the recommendation engine.

- Cloud Deployment: Leveraging AWS, we ensured high availability and scalability for the platform, accommodating Liquidity Digital's growing user base.

- Basic Frontend: We developed an intuitive frontend interface for the MVP, enhancing user experience while keeping the focus on essential features.

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Results

Our collaboration with Liquidity Digital yielded remarkable outcomes:

- 45% Increase in Deal Success Rate: The recommendation engine significantly boosted the success rate of deals initiated through the platform, resulting in more successful funding rounds.

- 85% Reduction in Deal Sourcing Time: Automation of deal recommendation reduced the time and resources required for identifying potential investments, enabling faster decision-making for their clients compared to before.

Conclusion

Our custom AI-driven deal recommendation engine redefined how Liquidity Digital approaches deal-making. With impressive statistics showcasing increased deal success rates and significant time savings, the platform has proven to be a game-changer in the industry.