Vellum vs. Athina

Vellum and Athina both focus on improving AI workflows, but they serve different functions. Vellum is designed for prompt management, offering a low-code interface that makes it easier for teams to refine AI interactions. Athina, on the other hand, specializes in structured prompt organization, helping teams maintain consistency and control over AI-generated outputs. While both platforms offer useful features, they also have limitations that may require additional tools to create a more complete AI development process.

However, there is another platform that offers a more robust and scalable solution. Sandgarden builds on the strengths of both Vellum and Athina while addressing their shortcomings, delivering a more flexible and efficient AI development environment. This comparison will examine how Vellum and Athina compare while introducing an alternative that enhances workflow efficiency, scalability, and security.

Vellum’s low-code AI prompt manager compared with Athina’s structured AI workflow.

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

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

Athina

Athina empowers teams to experiment, evaluate, and monitor AI-driven applications. With its internal IDE, Athina offers a suite of tools to create, manage, and evaluate datasets, prompts, and evaluations.

The platform also includes observability tools, allowing teams to monitor AI model performance, manage costs, and maintain quality over time. In sum, Athina helps businesses efficiently integrate high quality and reliable AI powered workflows into their applications.

That said, Athina is not without its drawbacks:

Onboarding requires a lot of trial and error
No seamless way of integrating customer data
Limited scalability for large-scale operations

View more Athina 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

Vellum and Athina each provide useful tools for AI development, but both have significant gaps that limit their effectiveness as comprehensive solutions. Vellum is designed to simplify prompt management with a low-code interface, making it accessible for users looking to refine AI interactions. However, it lacks robust version control, real-time analytics, and enterprise-grade security, making it challenging to scale AI applications efficiently. Athina, while offering structured prompt management, falls short in areas such as model evaluation, deployment flexibility, and advanced logging, requiring teams to integrate multiple third-party tools to fill these gaps.

Sandgarden removes these limitations by providing an all-in-one AI development environment that seamlessly integrates prompt management, analytics, and security into a single platform. Unlike Vellum and Athina, Sandgarden offers built-in version control, real-time monitoring, and enterprise-grade encryption, ensuring AI teams have full control over their workflows. With an API-first approach and flexible deployment options, Sandgarden enables organizations to scale efficiently while maintaining security and reliability. For teams looking for a comprehensive, future-proof AI development solution, Sandgarden is the superior choice.