Parea vs. Vellum

Parea and Vellum are two AI platforms designed to improve the way teams build and refine AI models, but they serve different functions. Parea focuses on testing and optimizing language models, helping teams continuously refine performance. Vellum, on the other hand, provides a low-code interface for managing prompts, making it easier to experiment with AI interactions. While both platforms offer valuable capabilities, they also come with limitations that may require additional tools or integrations to create a more complete AI workflow.

For those looking for a more comprehensive approach, another option stands out. Sandgarden combines the strengths of both Parea and Vellum while addressing their gaps, providing a more scalable and efficient AI development environment. This comparison will break down the key differences between Parea and Vellum while also introducing an alternative that offers greater flexibility, security, and long-term adaptability.

Parea’s AI testing system compared with 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

Parea

Parea empowers teams to test and continuously refine AI-driven applications. The platform streamlines a range of tasks, including the generation, evaluation, and optimization of prompts to boost their effectiveness.

Equipped with tools like API integration and analytics, users can track live data and obtain actionable insights, improving their development processes. Additionally, Parea provides customizable feature development, making it a good choice for teams aiming to scale their LLM-driven projects with efficiency.

That said, Parea is not without its drawbacks:

No seamless way of integrating customer data

Unwieldy for less technical users

Limited scalability for large-scale operations

View more Parea 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

Parea and Vellum each offer useful features for AI development, but both fall short of providing a fully comprehensive solution. Parea focuses on continuous testing and optimization of language models, helping teams refine AI performance over time. However, it lacks robust version control, structured logging, and security features necessary for enterprise-level deployments. Vellum, on the other hand, provides a low-code approach to prompt management, making it accessible for users who want a streamlined workflow. Yet, it sacrifices deeper functionality such as model evaluation, real-time analytics, and scalable infrastructure support.

Sandgarden removes these limitations by delivering an all-in-one AI development environment that ensures efficiency, security, and scalability. Unlike Parea and Vellum, Sandgarden integrates structured prompt management, real-time analytics, and robust version control within a single platform. Its enterprise-grade security, including encryption and access control, guarantees safe and scalable AI deployments. With an API-first approach and flexible hosting options, Sandgarden empowers teams to move quickly without sacrificing the technical depth required for advanced AI development. For organizations seeking a future-proof AI platform that balances flexibility and power, Sandgarden is the clear leader.