Rivet vs. Vellum

Rivet and Vellum are two AI development platforms that serve different purposes. Rivet provides a no-code environment for building AI workflows, making it accessible to teams that want to streamline development without heavy coding. Vellum, on the other hand, focuses on prompt management, offering a low-code approach to refining AI interactions. While both platforms bring value, they also come with limitations that may require additional integrations to create a fully functional AI development pipeline.

For those looking for a more comprehensive solution, there is another option worth considering. Sandgarden offers a more robust AI development experience, addressing the gaps left by both Rivet and Vellum. This comparison will break down their key differences while also exploring how an alternative like Sandgarden can provide a more flexible and scalable approach.

Rivet’s no-code AI tools versus Vellum’s low-code AI prompt management.

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

Vellum

Vellum offers a visual interface to generate AI workflows simply without extensive experience with LLMs. This allows engineering and product teams to effectively collaborate on delivering AI solutions for various business needs.

Vellum excels in simplifying the basic processes for working with LLMs. Prompt engineering, semantic search, prompt chaining, and RAG are basic tools useful to any business looking to experiment with AI. Ease of use is augmented by thorough documentation and tutorials, further enabling users of various abilities to contribute to a company’s AI initiatives.

That said, Vellum is not without its drawbacks:

Less capable with complex implementations
Limited flexibility and control over underlying infrastructure
Hosted deployment options only

View more Vellum 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 Vellum take different approaches to AI development, but both have notable shortcomings. Rivet offers a no-code visual programming environment, making it accessible to users without deep technical expertise, yet it lacks critical features such as version control, advanced analytics, and enterprise-grade security. Vellum, on the other hand, focuses on simplifying prompt management with a low-code approach but falls short in areas like model evaluation, logging, and infrastructure flexibility. Neither platform provides an all-in-one solution that balances ease of use with deep functionality.

With Sandgarden, teams get the best of both worlds—user-friendly development tools combined with enterprise-grade capabilities. Unlike Rivet and Vellum, Sandgarden integrates structured prompt management, real-time analytics, and robust security features, including encryption and access control. Its API-first approach ensures seamless scalability, while built-in version control and flexible deployment options make it a superior choice for AI teams that require both power and efficiency. For organizations looking to eliminate workflow inefficiencies and security concerns, Sandgarden stands as the most capable and future-ready solution.