AI · Finance · Decision Systems
I'm Everett
Cedarholm.
I like building things. Communities, teams, products, and the systems that help people move toward something together.
I like building things. Communities, teams, products, and the systems that help people move toward something together.
I've always gravitated toward environments with open ended tasks and 0-to-1 projects.
In 2019, I joined a pre-seed Sequoia/Lightspeed startup in Indonesia as the 10th employee and helped scale the company to more than 1,000 employees. I built departments from 0-to-1 focused on improving customer experience during rapid expansion before shifting my focus toward profitability, unit economics, and building systems that supported sustainable growth.
Today I'm building independently at the intersection of AI, finance, and decision-making. I experiment, ship prototypes, and develop tools that bring structure to messy information. Like every major shift in technology, the advantage goes to the builders willing to adapt early. I'm focused on learning fast and building alongside the wave as it grows.
Real work. Mostly scrappy. Always measurable. These are projects where I used AI to reduce uncertainty, speed up decisions, or automate the boring parts.
Building machine learning models to predict which Series A startups will achieve successful exits (IPO or acquisition) within 5–7 years, using Crunchbase-style data for VC deal screening. The work emphasizes strict temporal integrity (no data leakage), ensemble model comparison, and evaluation metrics aligned with real investment decisions like top-decile lift and calibrated probabilities.
ShopSherpa is a web application designed to streamline product recommendations by analyzing large volumes of user discussions and online content to surface clear, trustworthy buying guidance. It combines structured data processing with AI-driven summarization to turn fragmented customer opinions into actionable recommendations.
I'm a builder and scaler. I've built teams from scratch, prepared companies for scale, and driven profitability strategy.
Full résumé (PDF)
Download PDF ↓Short notes on what I'm testing, what broke, and what I learned. Mostly AI, markets, and how to build decision systems that don't lie to you.
An argument that if AI is already reshaping business, MBA programs need to adapt — moving beyond prompt usage and toward stronger technical foundations so students become real power users.
Lessons from Jakarta's Flooded Streets for Global Tech Resilience.
Always available to chat about AI, finance, or whatever's on your mind.
everett@cedarholm.ai