Participated · Series A · Sep 2025

Standard Fleet, headquartered in San Francisco, offers a fleet management platform that merges real-time telematics with digital key access and embedded payments, eliminating installation delays and separate hardware costs. The software targets rental, rideshare, leasing, insurance, and service fleets, giving operators a single system to track vehicles, control access, and handle transactions. Founded and led by CEO David Hodge, the company positions itself as a plug-and-play alternative to legacy fleet solutions that require aftermarket devices. Its product focus centers on streamlining vehicle data, driver permissions, and payment workflows within one interface. Standard Fleet plans to use newly raised capital to accelerate product development and scale go-to-market operations. The company did not disclose current revenue, customer counts, or other operating metrics in the article. With fresh funding and a roster of strategic mobility investors, Standard Fleet aims to deepen its footprint in the connected-vehicle sector.

Participated · Series B · Jun 2025

Deep Sentinel offers a proactive security platform that pairs proprietary AI video monitoring with live remote guards to detect and intervene on suspicious activity in real time. The company’s Bring Your Own Camera (BYOC) integration program, which supports third-party brands, now accounts for nearly half of all sales. Deep Sentinel says it has doubled sales bookings year over year, outpacing traditional players in an industry that typically grows 20–30% annually. The platform is trusted by hundreds of security integrators and thousands of businesses across the U.S. and claims to prevent thousands of crimes each month. Planned uses of the new capital include scaling the BYOC program, continued development of its AI models, and expanding its national commercial and residential footprint. Deep Sentinel offers a security technology platform that delivers the experience of a personal guard for homes and businesses through 24/7 live video monitoring by remote guards aided by proprietary AI. The company’s smart home security systems combine high-definition cameras, AI and human intervention to identify potential threats in real-time. Trained security guards review and respond to alerts from cameras positioned around a customer’s perimeter, communicate directly with owners and law enforcement, and aim to stop crime before an intruder enters the property. Led by CEO Dave Selinger, Deep Sentinel provides immediate human review of AI-flagged events to accelerate response. The company intends to use the new capital to accelerate its AI-powered virtual guard security offering. Deep Sentinel is developing cameras and a software system that use deep learning to evaluate and deter threats at the perimeter of a property. The company’s hardware is still in development and will be pre-trained before delivery; devices are designed to work together so analysis is focused only where threats are occurring or likely to occur. Deep Sentinel emphasizes local processing to reduce cloud compute needs, lower costs for consumers, and limit the amount of private data sent to the cloud. The system is intended to respond to threats with deterrents such as warnings or lights; the company considered drones but found the technology too nascent. Founder David Selinger positions the product as differentiated by user experience in a crowded market of intelligent cameras. The startup raised institutional capital to fund product development and market entry next year.

Participated · Series C · Jan 2025

Rad AI develops generative AI products for radiology, including Rad AI Impressions, Rad AI Reporting, and Rad AI Continuity, that are embedded into radiologists' workflows. Its Impressions product automates the impression section and saves radiologists more than an hour per shift on average. Rad AI Reporting includes features such as Omni Unchanged and Omni Report, which cut follow-up dictation time by 50%, reduce spoken words by 90%, and can double reporting speed. Rad AI Continuity automates tracking and coordination of incidental findings and has improved follow-up exam completion rates from approximately 30% to over 75% at users. The platform is trusted by thousands of U.S. radiologists and supports providers responsible for nearly half of all imaging volume in the U.S. The company is scaling enterprise deployments across hospitals and clinics with health-system partners to expand adoption and improve care coordination and efficiency. Rad AI develops generative AI solutions for radiology including Rad AI Impressions, Rad AI Reporting, and Rad AI Continuity that automate draft report text, reduce dictated words, and close the loop on actionable findings. Its flagship Rad AI Reporting can reduce dictated words by up to 90% and save providers up to 50% of their time; Rad AI Continuity has raised follow-up rates at health systems from about 30% to 75% or more. The company's products are used by thousands of U.S. radiologists daily and are deployed at health systems and practices that account for nearly 50% of U.S. medical imaging. Rad AI says it was the first to commercialize a generative AI product in healthcare and has been recognized by CB Insights and AuntMinnie for its products. The company is hiring across roles and plans to accelerate development and deployment of its generative AI technology to healthcare providers and systems globally. Rad AI builds software that generates radiology reports, aiming to cut the time radiologists spend on documentation. The company developed a proprietary LLM trained on radiology report datasets to automate findings and impressions. Rad AI says it began using LLMs in 2018 and positions itself as an early adopter of generative AI in radiology. Its products are used by about a third of U.S. health systems and nine of the 10 largest radiology groups. The company has raised over $80 million in total capital after a $50M Series B and plans to use the fresh funding to build a team to deploy a standalone radiology reporting solution. Rad AI is hiring staff to install and maintain the software and reports it has not lost a single customer since launch. Rad AI provides an AI platform that automatically generates customized impressions from dictated findings and clinical indications, learning each radiologist’s language preferences from prior reports. Its core offerings, Rad AI Omni and Rad AI Continuity, aim to improve report accuracy and consistency, surface significant incidental findings, and provide guideline-based follow-up recommendations. Omni injects the impression directly into the practice’s voice recognition software without extra clicks or windows, while Continuity closes the loop on follow-up by integrating into health systems’ EMRs and offering an outpatient platform. The company emphasizes time savings for radiologists, improved report processes, and reduced burnout. Rad AI is working with seven of the ten largest private radiology practices in the U.S. and plans to use new funding to further develop and commercialize its products. Rad AI, founded in 2018 by Doktor Gurson and Dr. Jeff Chang in Berkeley, Calif., builds machine-learning tools to automate repetitive radiology tasks. Its first product automatically generates the impression section of radiology reports, customized to each radiologist's preferred language. The company raised $4M in seed funding to build out its engineering team and expand the rollout of its first product to more radiology groups and customers. The round was led by Gradient Ventures, with participation from UP2398, Precursor Ventures, GMO Venture Partners, Array Ventures, Hike Ventures, Fifty Years VC and various angels. Current partners include Greensboro Radiology, Medford Radiology, Einstein Healthcare Network and Bay Imaging Consultants, along with other radiology groups yet to be announced.

Participated · Seed · Oct 2022

MakerDojo is a B2B SaaS data analytics platform founded in 2021 that automates blockchain data-extraction using an AI-backed engine. Its platform queries datasets across protocols such as Celo, Ethereum, Polygon, and NEAR, presenting results in easy-to-understand formats and pre-built dashboards to track tokens and dApps. The company aims to simplify developers' complex, error-prone, and capex-heavy blockchain data extraction processes. MakerDojo raised $1.5 million in a pre-seed round in October 2022 led by Leo Capital, with participation from UP2398 and Jan M. Leeman. Proceeds will be used for talent acquisition and product innovation to expand offerings for all major blockchain protocols. The company is headquartered in San Jose, California.

Participated · Series B · Oct 2021

Convex provides a cloud-based Atlas software platform that consolidates building attributes, permit history, property ownership, customer, asset, tenant and contact data into a property-centric view visualized in 3D maps. The platform equips users with no prior commercial-services knowledge with actionable insights to be productive immediately and gives managers increased visibility for coaching and directing teams. Convex’s solution covers more than 62 million commercial properties and is used by sales reps, managers, marketers and executives both in-office and in the field. Backed by workflow tools, the product helps teams uncover opportunities, pre-qualify prospective clients, build and manage pipelines, and win market share. Led by CEO and cofounder Charlie Warren, the company intends to use the new funding to expand hiring, scale Atlas and develop new products. To date Convex has raised $60M in total capital.