Caylent

At Together AI, we believe software quality comes from research-driven innovation and genuine collaboration. Our engineers and researchers work side-by-side, contributing to open-source advancements like FlashAttention, Mamba, and RedPajama while building infrastructure that powers the next generation of AI. We optimize for impact over hierarchy - meaning you'll own substantial technical challenges from day one, whether it's designing distributed inference engines or pioneering new model architectures. We're committed to open and transparent AI systems because we believe the best outcomes for society emerge from shared knowledge. Our purpose-built GPU cloud platform empowers developers and organizations of all sizes to train, fine-tune, and deploy generative AI models without lock-in. We foster a culture of deep technical curiosity where tackling frontier problems in distributed systems, model optimization, and AI infrastructure is the norm - not the exception.

At Baseten, we're a team of engineers and designers who believe the best products emerge when you work directly with the people using them. Our engineers spend time embedded with customers, learning from their operational challenges and turning those insights into infrastructure that just works. We ship daily, optimize obsessively, and measure our success by the real-world impact of the AI products running on our platform. We're an internationally diverse group of builders who take pride in our craft but not ourselves too seriously. Whether we're optimizing kernel-level performance for inference or building delightful developer tools, we believe software quality comes from small teams with real ownership. We optimize for shipping, not process - which is why we've been focused on rapid iteration and hands-on problem solving since day one.

SAP LeanIX provides a modern SaaS platform for Enterprise Architecture Management, giving organizations a single source of truth to navigate complex IT transformations. In an era where enterprises face constant pressure to modernize applications, migrate to the cloud, and upgrade ERP systems, LeanIX exists to eliminate the spreadsheet chaos that typically stalls these critical initiatives. The platform enables finance and IT teams to make data-driven decisions about their technology landscape, reducing risk and accelerating transformation timelines by up to 85%. Founded in 2012 in Bonn, Germany, LeanIX has grown from a bootstrapped startup to a global operation serving 700+ customers worldwide, including industry leaders across every sector. The company was acquired by SAP in November 2023, extending its reach and capabilities while maintaining its mission to democratize enterprise architecture for organizations of all sizes. With offices in Boston, London, Paris, Amsterdam, and Ljubljana, SAP LeanIX continues to innovate at the intersection of AI and enterprise architecture, recently introducing an AI agent hub to help organizations govern artificial intelligence across their technology stack.

Crusoe, founded in 2018 by Chase Lochmiller and Cully Cavness, is a vertically integrated AI infrastructure company that designs, builds, and operates purpose-built data centers and a cloud platform powered by clean energy. The company has raised billions in funding and targets gigawatt-scale data center campuses, positioning itself at the intersection of AI compute demand and sustainable energy supply. The technical stack spans data center design and construction, cloud platform engineering, and integration with hardware from partners including NVIDIA and AMD. Energy sources powering Crusoe's infrastructure include wind, solar, geothermal, and hydropower. The company's cloud platform is designed for organisations building AI solutions at scale. Crusoe's origins lie in a distinctive approach to energy recovery: the company initially converted wasted natural gas from oil fields into power for computing operations, including bitcoin mining. It has since pivoted to focus on clean energy sources and AI infrastructure, though its vertically integrated model - controlling energy sourcing, data center operations, and cloud delivery - reflects that founding philosophy. The company's stated mission is to accelerate the abundance of both energy and intelligence, an orientation that runs through its energy-first approach to infrastructure design and its emphasis on sustainability alongside computational scale.

CoreWeave is a specialized cloud platform founded in 2017 and built from the ground up to provide GPU-based infrastructure for artificial intelligence workloads. The company began as a cryptocurrency mining operation under the name Atlantic Crypto before pivoting entirely to AI infrastructure - a shift that has since placed it among TIME's 100 most influential companies. The platform is designed specifically for training and deploying large language models at scale, rather than adapting general-purpose cloud architecture to AI use cases. Its core offerings include GPU compute, a Kubernetes-based orchestration layer tuned for AI workloads, and custom storage solutions built to meet the demands of machine learning pipelines. CoreWeave operates data centers across the United States and Europe, serving AI research labs, enterprises, and startups. Engineering at CoreWeave spans a broad range of technical disciplines, including: AI infrastructure and GPU compute Cloud platform and data center operations Kubernetes-based orchestration Custom storage systems for ML workloads Large language model training and deployment The company draws its team from varied professional backgrounds - including commodities trading and infrastructure engineering - and operates with the stated conviction that cloud infrastructure designed for AI must differ fundamentally from what came before it.

In 2019, Edo Liberty was working as a research director at AWS and at Yahoo before that, where he witnessed the tremendous power of combining AI models and vector search to dramatically improve applications such as spam detectors and recommendation systems. While building custom vector search systems at enormous scales, he assumed there was already a packaged solution available for everyone else who didn't have access to the same engineering and data-science resources. To his surprise, there wasn't. This gap in the market led Edo to found Pinecone, creating the vector database category of solutions from scratch. The company was born from the recognition that developers and engineering teams of all sizes needed accessible storage and retrieval infrastructure for building and running state-of-the-art AI applications. This founding principle of accessibility drove Pinecone's evolution into a fully managed service known for its ease of use, enabling thousands of companies to ship AI applications faster and more confidently.