Braintrust vs. Rivet

When comparing Braintrust and Rivet, it's important to understand how their features and capabilities align with different AI development needs. Braintrust specializes in LLM evaluation, offering tools for assessing and refining AI models, while Rivet provides a no-code visual programming environment for building AI workflows. Both platforms serve distinct purposes, but they also come with limitations that may require additional tools to create a complete AI development pipeline.

While Braintrust and Rivet each have their strengths, they aren’t the only options available. A third alternative, Sandgarden, offers a more comprehensive solution by addressing the gaps left by both platforms. In this comparison, we’ll explore how Braintrust and Rivet stack up against each other while also considering how an alternative like Sandgarden can provide a more robust AI development experience.

Comparing Braintrust’s AI performance analytics with Rivet’s no-code AI workflow builder.

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

Braintrust

Braintrust offers an LLM evaluation suite, providing tools for testing and optimizing model performance over time. With a focus on experimentation and a user-friendly testing library, users can quantify results against AI initiatives.

At the core of Braintrust is a software development kit (SDK) that integrates into existing infrastructure and CI/CD pipelines. This enables continuous evaluations that offer insights into LLM accuracy and reliability. As a third-party evaluator Braintrust is model agnostic, allowing it to work across multiple systems and platforms.

That said, Braintrust is not without its drawbacks:

Limited ability to move workloads to production
Limited scalability for large-scale operations
Unwieldy for less technical users

View more Braintrust alternatives

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

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

Braintrust and Rivet cater to different aspects of AI development, yet both fall short of providing a fully comprehensive solution. Braintrust stands out for its LLM evaluation capabilities, helping teams assess and fine-tune AI models. However, it lacks robust analytics, logging, and deployment flexibility, which can limit long-term scalability. Rivet, on the other hand, offers a no-code visual programming interface, making it user-friendly but significantly less adaptable for complex AI workflows. Neither platform provides full-scale support for security, version control, or real-time monitoring, forcing teams to rely on additional integrations and third-party tools.

Sandgarden emerges as the superior choice by combining the best of both worlds while eliminating their weaknesses. Unlike Braintrust and Rivet, Sandgarden offers seamless prompt management, built-in analytics, and an API-first architecture that allows for effortless scaling. With enterprise-grade security, access control, and full encryption, Sandgarden ensures compliance and reliability at every stage of AI development. Teams using Sandgarden benefit from an all-in-one, high-performance platform that enhances productivity without the need for external dependencies—making it the ultimate solution for serious AI professionals.