Core Insights - CrowdStrike and NVIDIA announced the integration of Charlotte AI AgentWorks with NVIDIA Nemotron, enhancing their collaboration in AI technology [1] - The expanded partnership aims to extend the Falcon platform, providing protection and governance for AI agents developed with NVIDIA NeMo tools and third-party ecosystems [1] - This integration builds on CrowdStrike's comprehensive lifecycle protection for large language models (LLMs) within the NVIDIA Enterprise framework [1]

Core Insights - Profusa, Inc. is set to launch an AI-driven physician portal in early 2026 within the European Economic Area (EEA), integrating its Lumee™ oxygen monitoring technology with NVIDIA's NeMo for enhanced clinical workflows [1][4] - The company aims to provide real-time biochemistry data to improve healthcare outcomes, linking therapeutic decisions with immediate biochemical changes [2][4] - The portal will facilitate remote patient monitoring and enhance the accuracy of personalized sensor data by connecting with electronic medical records (EMR) [1][4] Company Overview - Profusa is a commercial stage digital health company based in Berkeley, California, focused on developing tissue-integrated sensors for continuous monitoring of biochemistry [5] - The company is led by experienced management and a scientific team, aiming to deliver affordable and long-lasting biosensors for personal and medical use [5] Technology and Features - The physician portal will translate raw optical signals into reliable biometrics, providing actionable clinical insights rather than just dashboards [3][4] - Key features of the portal include integration with EMRs, remote physiologic monitoring, and a longitudinal health data graph that combines various health data sources [7]

Solution Overview - DDN provides a one-click high-performance RAG (Retrieval-Augmented Generation) pipeline for enterprise use, deployable across various environments [1] - The RAG pipeline solution incorporates NVIDIA NIM within the NVIDIA Nemo framework, hosting embedding, reranking, and LLM models, along with a MILV vector database [2] - DDN Infinia cluster, with approximately 0.75 petabytes capacity, serves as the backend for the MILV vector database [3] Technical Details - Infinia's AI-optimized architecture, combined with KVS, accelerates NVIDIA GPU indexing [3] - The solution utilizes an NVIDIA AI data platform reference design to facilitate the creation of custom knowledge bases for extending LLM capabilities [4] - The one-click RAG pipeline supports multiple foundation models for query optimization [7] Performance and Benefits - Integration between DDN Infinia and NVIDIA Nemo retriever, along with NVIDIA KVS, results in faster response times, quicker data updates, and rapid deployment of custom chatbots [9] - The RAG pipeline enables detailed and accurate responses to specific queries, as demonstrated by the Infinia CLI hardware management features example [8][9]