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Dili Aims to Utilize AI for Automated Due Diligence

Revolutionizing Due Diligence: How Dili’s AI Platform is Reshaping Investment Strategies

Stephanie Song, formerly part of Coinbase’s corporate development and ventures team, knows the grind of daily due diligence tasks all too well. In an email interview with TechCrunch, she expressed her frustration: โ€œAnalysts burn the midnight oil working hundreds of hours doing the work that nobody wants to do.” Song, alongside Brian Fernandez and Anand Chaturvedi, ex-colleagues from Coinbase, co-founded Dili, a platform aiming to revolutionize investment due diligence and portfolio management for private equity and VC firms through AI automation.

Disrupting the Norm: Introducing Dili

Dili, a graduate of Y Combinator, has secured $3.6 million in venture funding from notable backers like Allianz Strategic Investments and Singularity Capital. Stephanie Song emphasizes the broad impact of AI on investment practices, stating, โ€œ[AI] affects all parts of an investment fund, from analysts to partners and back-office functions.” With VCs holding a substantial $311 billion in unspent capital and raising historically low funds, there’s a growing demand for innovative solutions like Dili to optimize investment strategies.

The Rise of AI in Due Diligence

AI’s role in due diligence is on the rise, with Gartner predicting that by 2025, over 75% of VC and early-stage investor reviews will incorporate AI and data analytics. While Dili isn’t the sole player in this field, Song emphasizes its unique approach, leveraging “first-of-its-kind” technology for high-accuracy tasks like extracting financial metrics from unstructured documents.

Trusting AI in Portfolio Management

However, the reliance on AI in decision-making raises concerns about accuracy and biases. Fast Company’s experiment with ChatGPT highlighted potential inaccuracies, while Harvard Business Review’s study revealed biases favouring white and male entrepreneurs in investment decisions. Additionally, some firms may hesitate to entrust sensitive data to third-party AI models due to confidentiality concerns.

Addressing Concerns and Expanding Horizons

To address these issues, Dili is continually refining its models to enhance accuracy and mitigate biases. Moreover, the platform plans to offer customization options for firms to train models on proprietary data, ensuring data privacy. Despite these challenges, Dili remains optimistic about its potential to unlock untapped opportunities in the private market data landscape.

Towards a Comprehensive Solution

Dili’s journey doesn’t stop at due diligence; it aims to evolve into an end-to-end solution for investor due diligence and portfolio management. With an initial pilot involving 400 analysts and users, Dili is poised to expand its capabilities and applications, envisioning a future where its technology revolutionizes the entire asset allocation process.
In conclusion, Dili’s innovative approach to leveraging AI in due diligence signifies a paradigm shift in investment strategies. While challenges persist, the platform’s commitment to enhancing accuracy and addressing biases underscores its potential to reshape the future of investment management.

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