Stephanie Song, formerly on the corporate development and ventures team at Coinbase, was often frustrated by the volume of due diligence tasks she and her team had to complete on a daily basis. Analysts burn the midnight oil working hundreds of hours doing the work that nobody wants to do, while funds are deploying less capital and looking for ways to make their teams more efficient while reducing operating costs.
The Birth of Dili
Inspired to find a better way, Song teamed up with Brian Fernandez and Anand Chaturvedi, two ex-Coinbase colleagues, to launch Dili (not to be confused by the capital of East Timor), a platform that attempts to automate key investment due diligence and portfolio management steps for private equity and VC firms using AI.
Dili, a Y Combinator graduate, has raised $3.6 million in venture funding to date from backers such as Khosla Ventures and Y Combinator, with participation from other notable investors like Marc Andreessen and Ben Horowitz.
How Dili Works
Dili’s platform utilizes a combination of natural language processing (NLP) and machine learning algorithms to automate the due diligence process. The platform integrates with existing systems to collect data on companies, allowing users to track key metrics such as financial performance, management team experience, and market trends.
The platform also includes features for deal sourcing, pipeline management, and investor relationship management, providing a comprehensive view of the investment pipeline.
Addressing Concerns Around AI
One of the major concerns around using AI in due diligence is the potential for "hallucination" – where the model generates information that isn’t actually present in the data. To address this concern, Song said that Dili is continuing to fine-tune its models, many of which are open source, to reduce instances of hallucination and improve overall accuracy.
She also stressed that private customer data isn’t used to train Dili’s models and that Dili plans to offer a way for funds to create their own models trained on proprietary, offline fund data. This approach is designed to alleviate concerns around data security and confidentiality.
Pilot Program and Future Plans
Dili ran an initial pilot last year with 400 analysts and users across different types of funds and banks. But as the startup expands its team and adds new capabilities, it’s angling to expand into new applications — ultimately toward becoming an ‘end-to-end’ solution for investor due diligence and portfolio management.
Eventually, the company believes this core technology can be applied to all parts of the asset allocation process, providing a comprehensive platform for investors to make more informed decisions.
Conclusion
Dili is tackling a significant challenge in the investment industry by automating the due diligence process using AI. With its innovative approach and commitment to addressing concerns around data security and accuracy, Dili has the potential to revolutionize the way investors approach deal sourcing and portfolio management.
As the company continues to expand its team and capabilities, it will be interesting to see how it adapts to the evolving needs of the investment industry and whether it can achieve its ambitious goal of becoming an end-to-end solution for investor due diligence and portfolio management.
Related Topics
- AI
- Funding
- GenAI
- Startup
- Startups
- Y Combinator