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As AI use cases continue to advance, the underlying architectures powering these innovations have grown increasingly complex. Designing intricate Compound AI systems that can handle evolving demands using an ever-expanding array of models, integrations, and workflows is challenging in traditional programming environments.
At deepset, our mission is to simplify the AI development lifecycle and help companies build composable, modular, and observable AI solutions for real-world applications. That’s why we built deepset AI Platform (formerly known as deepset Cloud), our end-to-end solution that accelerates the development and deployment of custom enterprise-grade AI applications. AI teams across industries are using deepset to significantly speed up the delivery of production-ready AI solutions.
Today, we’re proud to announce deepset Studio, the community version of deepset. deepset Studio is free to use and includes essential infrastructure and tooling from deepset to build and test AI prototypes.
deepset Studio is built on Haystack, our popular open-source AI framework. Any developer, data scientist, product manager, or AI engineer can use deepset Studio to architect a wide range of LLM applications. With deepset Studio, users can:
Building products with generative AI requires integrating a variety of complex models, writing custom components and integrations, and keeping track of the different prototype versions that need to be evaluated end-to-end. LLM orchestration frameworks like Haystack exist to provide the building blocks, integrations, and routing logic to facilitate this process. But for cross-functional AI teams, a platform that brings all of these tools together in a single interface and provides workflows to guide them through the building process - from design to deployment to testing - is critical.
Anyone can now sign up for deepset Studio for free and experience the ease of building in a unified environment firsthand. With sophisticated tools for building custom AI applications, AI engineers will see just how quickly they can develop a fully functional prototype in deepset Studio, allowing them to present a proof of concept to their team in record time. They can then export that prototype in their preferred format to develop it into a full-blown product, or take advantage of the rounded, powerful capabilities of the deepset platform, which adds advanced features such as side-by-side comparisons of different prototypes and enhanced scaling and data storage options.
As part of our launch, we’re proud to announce a native integration with NVIDIA AI Enterprise software. NVIDIA AI Enterprise users can optimize their deployments through deepset Studio’s integration with NVIDIA NIM microservices and the NVIDIA API catalog. Users can configure NIM microservice deployments and LLM inference directly in Studio. Check out our deployment guide for setting up NIM and Haystack pipelines on Kubernetes, streamlining deployment to any cloud or data center.
Any developer can register and use deepset Studio for free, unlocking an interactive environment to learn and explore Haystack components and pipelines, and build custom LLM applications.
To get access, sign up here.
Don’t forget to join our Discord community of AI enthusiasts and builders to share your deepset Studio questions and experience!
Note: deepset Studio is a free tool with usage limitations. It is ideal for prototyping your AI applications with the infrastructure to host your pipelines while you test and experiment. To work without limits and expand your Studio experience with broader enterprise deployment and scaling options, we invite you to explore deepset AI Platform.