Private-market investing is still running on PDFs, scattered spreadsheets, and manual models, while public markets operate with real-time analytics and platforms like Bloomberg. The gap keeps widening, and AI seems like the obvious fix.

But as Olivier and Naunidh explain, most of the real problems in private markets aren’t technical. They’re about trust, workflow, and the quality of the underlying data.

Tetrix was built to solve those problems. In just a year, the team has grown 10x, signed dozens of institutional clients, and developed a platform that automates the most painful parts of data collection and analysis, while keeping people in the loop where judgment matters most.

Instead of chasing hype, they spent months speaking with more than 400 investors, from VCs and LPs to asset managers, to understand where decisions actually break down. The answer wasn’t “more AI.” It was cleaner data, clearer context, and tools investors could rely on.

What You’ll Learn

- Where AI really helps: How Tetrix automates the slow, manual parts of private-market workflows and where human insight is still essential.

- Why private-market data is so messy: And how better structure and context unlock stronger, faster analysis.

- How to build AI people trust: Why transparency, accuracy, and deep customer understanding matter more than any single model.

- How to scale in a conservative industry: Lessons from 400+ conversations, fast iteration, and staying close to real investor workflows.

Olivier and Naunidh’s story is a reminder that the future of private markets won’t be fully automated. It will be augmented, pairing AI with the human judgment that drives the best decisions.

Learn more

Website: tetrix.co

LinkedIn: Olivier Babin | Naunidh Bhalla