Most of the AI conversation in private equity has focused on deal sourcing, diligence, and value creation. But another transformation is happening inside portfolio teams — and it's about information. Specifically, the gap between when something starts to go wrong at a portfolio company and when the GP actually finds out.

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In this panel, Stu Willson is joined by Yann Magnan, CEO and Co-Founder of 73 Strings (AI-powered valuation and monitoring platform, backed by Goldman Sachs, Blackstone, Fidelity International, Golub and Hamilton Lane), and Joe Zein, Co-Founder of Soal Labs (custom AI infrastructure for PE and private credit). They dig into why portfolio monitoring is uniquely hard, why the data model matters more than the model, and what the state of the art will look like in 18 months.
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Chapters:

00:00 – Intro & the 60-day information gap
02:33 – Why monthly monitoring is brutal: data, process, bandwidth
06:10 – The real bottleneck at the GP: how reports actually get assembled
09:20 – Best and worst case timelines for a quarterly close
10:44 – Is the problem cadence, or infrastructure?
13:40 – Signals: what shows up before EBITDA moves
18:57 – New data sources, covenants, and the credit boom
21:31 – Why "vibecoded" monitoring tools fail
25:20 – The 100% accuracy problem in private capital
26:55 – What a robust data model actually looks like
29:45 – Moving from file systems to governed structured data
35:49 – Entity resolution across 73 Strings, Salesforce, and the file system
37:00 – Light vs. frontier LLMs: which do you actually need?
40:17 – Confidentiality, enterprise plans, and the open-source option
43:59 – What most people miss about AI and portfolio monitoring
46:29 – Portfolio monitoring in 18 months
49:35 – One thing to start doing right now
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Keywords: Stu Willson, Stuart Willson, Just Curious, Pluris, Yann Magnan, Joe Zein, 73 Strings, Soal Labs, portfolio monitoring, private equity, private credit, AI in private equity, alternative investments, GP reporting, NAV reporting, portfolio valuation, entity resolution, data model, LLMs in finance, AI infrastructure, GenAI, data governance, vibecoding, covenant monitoring, LP reporting, AI agents
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