Participated · Series A · Dec 2023

mAy-I develops machine-learning–based human tracking solutions that analyze CCTV footage to generate insights on demographics, foot traffic, dwell times, behaviors, and product interactions. Its core product is the mAsh video processing AI solution, which processes visitor data from cameras installed in physical spaces. The company positions its technology to help clients understand movement patterns and customer interactions in venues and stores. mAy-I intends to use new funding to support business development, expand its customer base, and enhance its AI capabilities. The company raised KRW 6.0 billion in a Series A round in December 2023. The team lists a company website at https://may-i.io/.

Participated · Series B · Oct 2022

Classum provides a Software-as-a-Service interactive learning platform designed for corporations and universities to maximize communication and engagement. The platform supports social media-style communication features and selective anonymity to lower barriers in Q&As and knowledge sharing. It also uses AI to curate FAQs and deliver data-driven insights into the dynamics of each learning environment. Founded in 2018 and led by CEO Youjin Choi, Classum is used by more than 6,000 organizations across 32 countries, including Seoul National University, KAIST, Yonsei University, Samsung Electronics, LG Academy, Prudential, Shiseido and World Vision. The company raised $11M in Pre-Series B funding and intends to use the proceeds to attract talent and scale its presence across additional key geographies.

Participated · Equity · Apr 2020

THE.WAVE.TALK has developed live bacteria sensing and IoT turbidity testing technology that enables rapid antibiotic susceptibility testing (AST) and minimum inhibitory concentration (MIC) testing using equipment that costs several hundreds of USD. The company is working with four major local governments to complete a testbed by June that uses an IoT sensor to automatically measure household water turbidity. It is pursuing Good Manufacturing Practice (GMP) and Korea’s Ministry of Food and Drug Safety certification for antibiotic inspection equipment, including a “Bacometer AI” that can diagnose urinary tract infection in under 3 hours and perform AST/MIC in under 6 hours. THE.WAVE.TALK intends to use the new funds to continue product development, construct a big data network to automatically measure household water quality via IoT sensors, and expand into the global market. The company is led by CEO Kim Young-dug Kim and has raised a total of approximately US$6m to date.

Participated · Series A · Mar 2020

Stellar Cyber offers an AI-driven, open and unified SecOps platform that consolidates security data and integrates with more than 500 third-party security tools. The platform combines machine learning, agentic AI, and human-augmented decision-making to improve analyst productivity and reduce false positives, with the company citing analyst productivity improvements of more than 80% and false positives reduced by over 90%. Stellar Cyber is purpose-built to serve managed security service providers (MSSPs) and enterprise teams and is trusted by one-third of the world’s top 250 MSSPs. The company says its technology supports over 14,000 organizations across more than 50 countries. Founded in 2015, Stellar Cyber is backed by Highland Capital Partners, Susquehanna Ventures and Valley Capital Partners. Following the new $25 million delayed-draw senior credit facility from Horizon Technology Finance, Stellar Cyber plans to accelerate platform development and expand its go-to-market reach.

Led · Seed · Aug 2017

GoodTime provides an AI-based interview scheduling and hiring experience solution that automates meeting coordination and measures DE&I in the interview process. The company says its platform can reduce time-to-hire by as much as 50% and save up to $500,000 per year in talent acquisition costs. GoodTime highlights customers including Box, Shopify, Zoom, Dropbox, Instacart, Slack, Pinterest, Stripe, Atlassian and Snapchat. It positions itself as the only HRtech solution that provides a way to measure and manage diversity, equity and inclusion for interview scheduling. The company plans to use new funding to accelerate innovation in hiring/candidate-experience solutions and to expand go-to-market growth across industries. GoodTime said it expects new innovations to launch in the second half of 2021. GoodTime builds an interview scheduling and management platform that uses natural language processing and the calendar as its organizing principle to link candidates with the right interviewers. The product factors in applicant and interviewer data such as gender, ethnicity, university, and prior work history to improve matching and coordination. Recruiting coordinators can manage the end-to-end interview process to reduce friction and speed hiring decisions. Customers like Airbnb and Dropbox have adopted the platform and reported applicants confirming interviews within three hours and time-to-hire reductions of about 40 percent. The company was founded by Ahryun Moon, Jasper Sone, and Peter Lee; Moon is CEO and previously worked as a recruiting coordinator at MuleSoft, Airbnb, and Dropbox. GoodTime is based in San Francisco, has 18 employees, graduated from the Alchemist Accelerator, and has reached profitability on the strength of its existing customers. GoodTime is building a calendar-centric HR tool that uses natural language processing to match job applicants with appropriate interviewers. It integrates with applicant tracking systems and extracts candidate and employee details from spreadsheets and documents to inform pairings based on prior work or university affiliations. The product also focuses on classifying calendar events to separate important meetings from reminders and other low-value items, enabling human-in-the-loop prioritization. GoodTime has early users and paying customers, including Airbnb, and has found product-market fit with Stripe, Thumbtack, and others. The team plans to hire in sales and engineering, with a particular emphasis on machine learning. The company raised a $2M seed to support product development and growth.