Rivet vs. Haystack

Rivet and Haystack serve different roles in AI development, each with its own strengths. Rivet offers a no-code interface for building AI workflows, making it accessible to teams that want to streamline development without heavy coding. Haystack, on the other hand, specializes in search and retrieval-based AI applications, excelling at processing large-scale queries. While both platforms provide useful features, they also have gaps that may require additional tools to create a more complete AI solution.

For teams needing a more versatile and scalable approach, another option stands out. Sandgarden goes beyond the capabilities of both Rivet and Haystack by offering a more integrated AI development environment with greater flexibility and advanced features. This comparison will break down the key differences between Rivet and Haystack while introducing an alternative that better meets the demands of modern AI workflows.

Rivet’s AI workflow automation versus Haystack’s AI search and retrieval platform.

Feature Comparison

Prompt Management

LLM Evaluation

Version Control

Analytics

Tracing

Metrics

Logging

API First

Self-Hosted

On-Prem Deployment

Dedicated Infrastructure

Access Control

SSO

Data Encryption

Rivet

With Rivet developers can design, debug, and collaborate on LLM prompt graphs, and deploy them in their own environment. The tool’s graph-based approach helps teams quickly identify performance and reliability issues across a range of workflows.

As a prompt IDE, Rivet simplifies the iteration process and allows prompt engineers to work with software developers to build AI agents. Alongside this is Trivet, a testing library for programmatically running tests on Rivet projects, providing a way to validate the functionality of their graphs. In sum, Rivet helps businesses efficiently integrate performant and reliable AI powered workflows into their applications.

That said, Rivet is not without its drawbacks:

Limited ability to move workloads to production

Limited scalability for large-scale operations

Can be cumbersome with a fair amount of manual work needed

View more Rivet alternatives

Haystack

Haystack is able to manage large datasets and deliver fast, accurate search results. Common use cases include semantic search, question answering, and RAG. It supports various search backends and offers tools for indexing, querying, and retrieving data.

At its core, Haystack’s focus is on efficiency and scalability. It’s designed to handle volume in both datasets and queries while providing quick response times. It continually evolves through contributions from an active OSS community, and is supplemented by a range of tutorials and example projects.

That said, Haystack is not without its drawbacks:

Use cases limited to search and retrieval
No implementation in programming languages other than Python
Documentation is comprehensive but unwieldy

View more Haystack alternatives

Sandgarden

Sandgarden provides production-ready infrastructure by automatically crafting the pipeline of tools and processes needed to experiment with AI. This helps businesses move from test to production without figuring out how to deploy, monitor, and scale the stack.

With Sandgarden you get an enterprise AI runtime engine that lets you stand up a test, refine and iterate, all in support of determining how to accelerate your business processes quickly. Time to value is their ethos and as such the platform is freely available to try without going through a sales process.

Conclusion

Rivet and Haystack serve different purposes in AI development, but both have gaps that limit their effectiveness as complete solutions. Rivet’s no-code interface is great for quick prototyping, yet it lacks essential capabilities like advanced version control, detailed analytics, and enterprise-grade security, making it difficult to scale. Haystack, while powerful for search and retrieval-based AI applications, falls short in areas such as structured prompt management, logging, and secure deployment. Both platforms require additional integrations and manual workarounds to achieve a fully functional, enterprise-ready AI workflow.

Sandgarden eliminates these inefficiencies by delivering a fully integrated AI development environment that combines the best of both Rivet and Haystack while addressing their weaknesses. Unlike its competitors, Sandgarden offers robust prompt management, real-time analytics, built-in security, and seamless deployment options—all in a single, scalable platform. With an API-first architecture, enterprise-grade encryption, and flexible hosting solutions, Sandgarden ensures that teams can build, deploy, and manage AI models with ease. For organizations looking for a truly comprehensive and future-proof AI solution, Sandgarden is the clear leader.