Private equity
AI solutions for private equity
Using Data to Drive Private Equity

Join celebrated data scientist Drew Conway, Head of Data Science for Two Sigma Private Investments and inventor of the Data Science Venn Diagram, in conversation with Jaclyn Rice Nelson, co-founder of Tribe AI, as they discuss the place of data science in the world of private equity.

Drive success at every stage of the deal pipeline

Tribe can help you leverage machine learning to identify potential investment opportunities, enhance due diligence, and support portfolio companies.

Learn how Tribe built an investment engine using public data for a PE firm

A leading PE firm came to Tribe with a specific challenge: to build an ML-driven toolkit that would give them unique insights into one particular vertical of interest using only publicly available data.

Recent private equity projects


Automate pricing for PE-backed insurance MGA

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Source new deals using  ML-driven toolkit for top PE firm

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Act as due diligence partners to determine value of data

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Advise on Generative AI adoption across portfolio

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How Tribe can help

Deal sourcing

Machine learning algorithms can analyze large amounts of public and proprietary data to surface potential investments. This optimizes analysts time and gives teams unique insights into the market.

Due diligence

Streamline the due diligence process by bringing in experts to evaluate technical data, analyze post-investment opportunities, and use ML-powered investment hypotheses to move quickly and confidently in a crowded market.

Portfolio management

Support portfolio companies by using data-driven analytics to inform forecasting, implementing dynamic algorithms based on user behavior to optimize pricing, and automating highly manual processes to streamline operations and drive value.

Risk management

Data analysis can  identify patterns and trends that may indicate potential risks in your portfolio or potential investments and allow for prompt action to mitigate them.
Work with the best talent in AI
Data Science Researcher

Postdoc researcher at Princeton

Research at Microsoft Research

Quant research, Software tech, Logistics
AI researcher

AI researcher at Sony

PhD in computational physics

Privacy, Data science, Analytics
AI Researcher

AI and research at Meta,
Allen AI, and Palantir

CV, NLP, ML Engineer

VP of Eng at Carta

Head of Eng at Nova

Blockchain, Fintech, Advisor
Senior Data Scientist

Data at Google

Launched Apple card at Apple

Data infra, Deep learning
ML Engineer

Deep Learning Scientist at Ravel Biotech

Researcher at Harvard Medical School

LLMs, Genomics, Reinforcement learning
ML and Software Engineer

Worked for Google Brain

and Facebook AI Research

Neural Networks, Computer Vision, Transformers
ML Engineer

ML Engineer at Meta

Co-founder Habiter (YC S20)

NLP, LLM, Neural networks, Deep learning
Beyond the [12%] premium lift, going through this exercise [with Tribe] really affirmed for us how much more we can do with data and machine learning.
We got so much more out of this project than we thought we would. And that’s in large part to the quality of the people Tribe brought in.
[Working with Tribe] gave us insights on our book of business and uncovered more areas we can use data to make smarter decisions moving forward.
It’s very rare you meet people like Tribe engineers who have the technical skills to understand your data, turn it into something actionable, and also communicate the value to us as the business guys.

Driving innovation with AI

Applied AI

How data science drives value for private equity from deal sourcing to post-investment data assets

Applied AI

How to Evaluate Generative AI Opportunities – A Framework for VCs


Stackoverflow: ML and AI consulting-as-a-service (ep. 541)

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