The moment has finally come as Artificial Intelligence has shifted left, making AI capabilities readily available to builders everywhere. To harness this power, a reliable and composable data platform is needed, which is where MongoDB Atlas comes in. The new Vector Search capability allows querying data based on semantics or meaning, rather than the data itself, by representing any form of data numerically as a vector that can be compared using algorithms. This unlocks a whole new class of capabilities, such as finding similar values in text, audio, image, or video data, enabling applications like "give me movies that feel sad" or "give me images that look like...". With Vector Search natively built into MongoDB Atlas, developers don't need to copy and transform their data or manage a new infrastructure, but can utilize powerful capabilities within a battle-tested platform. The capability also interacts with the ecosystem through supported frameworks and plugins, such as LangChain and LlamaIndex, and is announced in Public Preview today with plans for future exciting announcements and general availability.