Introducing deepset Studio

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 Cloud, our end-to-end platform that accelerates the development and deployment of custom enterprise-grade AI applications. AI teams across industries are using deepset Cloud to significantly speed up the delivery of production-ready AI solutions.

Today, we’re proud to announce deepset Studio, the community version of deepset Cloud. deepset Studio is free to use and includes essential infrastructure and tooling from deepset Cloud to build and test AI prototypes.

What is deepset Studio?

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:

1. Access Haystack’s comprehensive library of components and integrations to build powerful AI pipelines.
2. Create custom components specific to their businesses that seamlessly integrate in their AI pipelines.
3. Leverage pre-built pipeline templates for common use cases such as Retrieval Augmented Generation (RAG).
4. Upload data to or use sample data sets to test pipeline performance.
5. Use deepset’s managed vector database or connect to external databases like Elasticsearch, Pinecone, Qdrant, and Weaviate.
6. Design AI pipelines with a user-friendly drag-and-drop UX that maps 1:1 to corresponding code views.
7. Deploy AI pipelines instantly with one click on deepset’s secure hosted cloud infrastructure.
8. Test and debug prototypes in deepset’s Playground environment.
9. Share prototypes with end users to collect feedback and refine their AI solutions.
10. Export the final setup as a YAML file or Python code for use in different environments.

The advantages of working in deepset Studio

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 Cloud platform, which adds advanced features such as side-by-side comparisons of different prototypes and enhanced scaling and data storage options.

Optimize deployments with NVIDIA AI Enterprise

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.

Sign up today

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 Cloud.