Stephanie Song, previously a member of the corporate development and ventures team at Coinbase, found herself frustrated by the overwhelming amount of due diligence tasks that she and her team needed to complete on a daily basis. In an email interview with TechCrunch, Song explained, “Analysts spend countless hours working on tasks that no one wants to do, while funds are deploying less capital and seeking ways to make their teams more efficient and reduce operating costs.”
Motivated to find a better solution, Song partnered with former Coinbase colleagues Brian Fernandez and Anand Chaturvedi to launch Dili, a platform that uses AI to automate key investment due diligence and portfolio management tasks for private equity and VC firms.
Dili, a Y Combinator graduate, has secured $3.6 million in venture funding from investors including Allianz Strategic Investments, Rebel Fund, Singularity Capital, Corenest, Decacorn, Pioneer Fund, NVO Capital, Amino Capital, Rocketship VC, Hi2 Ventures, Gaingels, and Hyper Ventures.
Song emphasized that AI has a significant impact on all aspects of an investment fund and that investment professionals are looking for ways to gain a competitive edge. Dili, she believes, has the potential to emerge as a solution for funds in a challenging macro environment.
While Dili is not the first to apply AI to the due diligence process, Gartner predicts that by 2025, over 75% of VC and early-stage investor executive reviews will be informed using AI and data analytics.
Dili utilizes GenAI, specifically large language models similar to OpenAI’s ChatGPT, to streamline investor workflows. The platform catalogs a fund’s historical financial data and investment decisions, leveraging AI to automate tasks such as parsing databases of private company data, handling due diligence request lists, and conducting industry benchmarking on a firm’s backlog of deals.
Despite the potential benefits, there are concerns related to the use of AI in portfolio management. Fast Company reported inaccuracies in AI-generated summaries, and bias in decision-making that favors certain demographics over others.
To address these concerns, Song stated that Dili is continuously refining its models and protecting customer data privacy. She also emphasized that Dili plans to offer an option for funds to create their own models trained on proprietary fund data.
Dili conducted an initial pilot with 400 analysts and users across various types of funds and banks and is looking to expand into new applications. Ultimately, Song sees Dili evolving into an “end-to-end” solution for investor due diligence and portfolio management, with the potential to be applied to all parts of the asset allocation process.
