Standard Metrics (formerly Quaestor) is a San Francisco-based financial data and portfolio monitoring platform for venture capital. It automates the messy work of collecting, standardizing, and benchmarking metrics from private portfolio companies, giving investors real-time performance data and giving founders a single source of truth for investor reporting. More than 100 VC firms track thousands of portfolio companies on the platform, which now connects directly to LLMs like Claude and ChatGPT through a Model Context Protocol server.
Avant-garde Health is a Boston-based healthcare data analytics company whose CareMeasurement platform helps hospitals, ambulatory surgery centers and physicians measure the true cost, quality and processes of surgical care - then turn those insights into measurable savings and better patient outcomes. Founded in 2014 out of value-based care research at Harvard Business School, the company applies Time-Driven Activity-Based Costing (TDABC) across EMR, financial, claims and patient-reported outcomes data to reveal what was previously invisible inside the operating room and the care pathway around it.
Matt Schulman is the Founder and CEO of Pave, the AI-powered compensation platform he built after watching coworkers at Facebook struggle to understand their own stock options. Starting with a cold email to 200 executives in 2019 (59 replied within 24 hours), he grew Pave into a $1.6 billion company with 3,500+ customers and $471M in total funding - making it the largest compensation data provider for private companies in the world after acquiring Option Impact from Morgan Stanley in 2022.
Pave is a San Francisco-based compensation management platform that helps companies plan, communicate, and benchmark employee pay in real time. Founded in 2019 by ex-Facebook engineer Matt Schulman, the company replaced HR's tangle of spreadsheets with live market data drawn from thousands of HRIS integrations, and now powers compensation decisions at Alphabet, Stripe, Databricks, Snowflake, Roblox, and thousands of others.
Mohamed Elgendy is the Co-Founder and CEO of Kolena, a San Francisco-based AI testing and validation platform that raised $21M to help enterprises build reliable, trustworthy AI systems. An Egyptian-American technologist and author of the widely-read 'Deep Learning for Vision Systems' (Manning Publications, 20,000+ copies sold), Elgendy cut his teeth building AI/ML organizations at Amazon, Twilio, Rakuten, and Synapse (acquired by Palantir) before founding Kolena in 2021. His mission: bring software engineering rigor - unit testing, regression analysis, scenario-level validation - to a field that has long relied on aggregate accuracy scores that mask real-world failures.
Jason Ding is the Senior Vice President of Engineering at Salesforce, leading the engineering teams behind Sales Cloud, Service Cloud, and Revenue Cloud — the backbone of the world's largest CRM platform. A PhD computer scientist turned performance engineering pioneer, he set nine SPEC benchmark world records at Cisco, helped drive UCS to $1 billion in revenue in under three years, and is now steering Salesforce's engineering toward a future of AI agents and billion-transaction-per-day scale. With 14+ years at Salesforce and deep roots in academia and chip-level performance work at Intel, Ding brings a rare combination of theoretical rigor and enterprise execution.