Latitude AI

At Rad AI, we believe the best healthcare AI is built by the very clinicians who use it every day. Founded in 2018 by Dr. Jeff Chang - the youngest radiologist in U.S. history - and serial entrepreneur Doktor Gurson, Rad AI grew from a simple observation: radiologists spend 75% of their time dictating reports instead of analyzing images. Our team of radiologists, engineers, and healthcare leaders work side-by-side to build solutions that feel less like software and more like an intelligent assistant designed by colleagues who understand the nuances of radiology workflow. We're not just shipping code - we're shipping relief. Our flagship products, Rad AI Impressions, Reporting, and Continuity, save radiologists over 60 minutes per shift by automatically generating impression sections customized to each physician's unique language style. The impact has been immediate: 84% of our users report reduced burnout, and we've helped health systems like Cone Health achieve 100% coverage for incidental findings while generating millions in additional revenue. With over $140M in funding from Khosla Ventures, Gradient Ventures, and World Innovation Lab, and recognition on Deloitte's Fast 500 and CNBC's Disruptor 50 list, we're scaling rapidly while staying true to our physician-led roots. Our engineers deploy to production daily, collaborate across functions with minimal bureaucracy, and maintain a remote-friendly culture optimized for focus, not facetime.

At Skild AI, we're building the world's first foundation model for robotics - a universal robot brain that can control arms, humanoids, and quadrupeds alike. Founded in 2023 by Carnegie Mellon professors Deepak Pathak and Abhinav Gupta, our team combines deep academic research with a relentless drive to bring physically-grounded intelligence to the real world. We believe in tackling robotics' hardest problems through massive simulation and cutting-edge machine learning, creating systems that learn from observation and adapt instantly to new bodies and environments. We work at the intersection of robotics, computer vision, and deep learning, attracting engineers and researchers who want to see their algorithms operate in the physical world, not just on servers. Our team values technical excellence, collaborative problem-solving, and the ambition to build what OpenAI has done for digital intelligence - but for robots. Backed by $300M in Series A funding and partners including NVIDIA and Amazon, we're moving fast to create the omni-bodied intelligence that will transform industries from manufacturing to logistics.

Sensi.AI is the world's first 24/7 Care Copilot, transforming home care through advanced audio AI technology that helps seniors age safely in place. The company's virtual care agent uses privacy-safe audio monitoring - not cameras - to detect emergencies, identify health changes, and provide actionable insights to care teams. With over 15 million interactions and 700,000 hours of audio training data, Sensi's sophisticated algorithms can identify falls, UTIs, cardiac events, mental distress, and early signs of dementia with remarkable accuracy. The system empowers home care agencies to reduce hospitalizations by 70%, increase revenue by 20%, and achieve 85% client satisfaction rates through proactive, data-driven care. Having raised $100M in total funding including a recent $45M Series C round led by Qumra Capital, Sensi.AI has rapidly scaled to become the trusted partner for over 80% of major U.S. home care networks. The company's three-part solution - unobtrusive in-home audio pods, verticalized AI models trained on clinician-labeled senior care data, and a real-time care copilot platform - enables agencies to deliver better care while improving operational efficiency. By bridging the critical gap between human caregivers and intelligent technology, Sensi is revolutionizing how an aging population receives support, ensuring dignity, independence, and peace of mind for millions of seniors and their families.

FAR.AI exists to solve one of humanity's most urgent challenges: ensuring that advanced AI systems remain safe and beneficial as they become increasingly powerful. The rapid advancement of AI technology poses existential risks that require coordinated, technical solutions. FAR.AI conducts frontier alignment research to improve the safety and security of AI systems through technical breakthroughs in model evaluation, interpretability, robustness, and value alignment - addressing fundamental issues like jailbreaks, toxic outputs, and the black-box nature of modern models before they become unmanageable. Unlike many research organizations that focus on a single approach, FAR.AI pursues a diverse portfolio of high-potential research agendas that sit between individual academic projects and for-profit initiatives. Through FAR.Research, FAR.Labs (a Berkeley coworking space), and FAR.Futures (global events and policy initiatives), the organization fosters collaboration among researchers, policymakers, and industry leaders worldwide. Since July 2022, FAR.AI has produced over 40 influential academic papers at venues like NeurIPS, ICML, and ICLR, while driving practical change through red-teaming partnerships with frontier model developers and government AI safety institutes.

Fractional AI exists to solve one of the biggest bottlenecks in enterprise AI adoption: the talent gap. While every C-suite recognizes that AI could transform their business, most companies lack the elite engineering talent needed to build production-grade AI systems. Fractional AI bridges this divide by deploying world-class engineers who specialize in applied generative AI - turning experimental projects into measurable competitive advantages. They don't just advise; they build, shipping custom AI solutions that automate workflows, reduce costs, and unlock revenue streams that off-the-shelf tools can't touch. What makes Fractional AI different is their services-first model and obsession with engineering excellence. Rather than forcing companies into a one-size-fits-all product, they embed directly with client teams to solve their specific problems - whether that's automating content moderation for Change.org, building API connectors for Airbyte, or reducing LLM hallucinations by 80% for Zapier. Their San Francisco-based team of former founders, CTOs, and senior engineers brings cross-industry expertise that internal teams can't match. They see patterns across companies, stay on the bleeding edge of what actually works in production, and transfer that knowledge back to their clients. The mission is clear: inspire an elite team of engineers to solve the world's most valuable problems using AI, and make every company they work with 2-10x more productive in the process.

Lightning AI builds the first operating system for AI development. The company behind PyTorch Lightning provides an end-to-end platform that streamlines the entire machine learning workflow - from idea and prototyping to training, deployment, and production scaling. Lightning eliminates infrastructure complexity by providing cloud-based GPUs, collaborative development environments, and integrated tools that let developers focus on building intelligent systems rather than managing servers. The platform serves over 10,000 organizations globally, ranging from solo researchers to Fortune 500 enterprises. Through its merger with Voltage Park, Lightning combines developer-first software with cost-efficient, large-scale compute infrastructure. The company has raised $127 million from investors including Coatue, Index Ventures, Bain Capital Ventures, Firstminute, Cisco Investments, JP Morgan, K5 Global, and NVIDIA. Lightning operates globally with offices in New York, San Francisco, Seattle, and London.