Vellum vs. HoneyHive

Vellum and HoneyHive offer distinct capabilities in AI development, but their core functions differ. Vellum is built for prompt management, providing a low-code solution that allows teams to refine AI interactions with greater control. HoneyHive, in contrast, focuses on AI-driven automation, helping businesses streamline workflows and optimize operations. While both platforms bring value, they also come with limitations that may require additional tools or integrations to achieve a complete AI development process.

Instead of piecing together multiple solutions, Sandgarden provides a more advanced and adaptable AI development environment. It extends beyond the capabilities of Vellum and HoneyHive by offering a more integrated approach that enhances efficiency, security, and scalability. This comparison will break down the key differences between Vellum and HoneyHive while introducing an alternative that ensures a smoother, more future-proof AI workflow.

Vellum’s low-code AI prompt system versus HoneyHive’s AI-driven workflow automation.

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

HoneyHive

HoneyHive provides evaluation, testing, and observability tools for teams building GenAI applications. It allows users to trace execution flows, customize event feedback, and create or fine-tune datasets from production logs. Businesses can leverage these tools to strengthen the quality of their AI workflows.

Along with a monitoring suite, HoneyHive offers a prompt management and playground feature. This helps simplify the iteration process and gives prompt engineers and developers a collaborative workspace to run and evaluate prompts. In sum, HoneyHive helps teams efficiently integrate performant and reliable AI powered workflows into their applications.

That said, HoneyHive is not without its drawbacks:

Doesn’t facilitate building new LLM-based applications
Limited to teams with existing AI expertise
Limited deployment options

View more HoneyHive 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 HoneyHive offer useful capabilities for AI development, but both fall short of providing a complete, enterprise-ready solution. Vellum is designed to simplify prompt management with a low-code approach, making it easier for teams to fine-tune AI interactions. However, it lacks critical features such as version control, real-time analytics, and enterprise-grade security, limiting its ability to support large-scale AI applications. HoneyHive, while focused on AI automation, does not provide structured prompt management, robust logging, or flexible deployment options, making it less adaptable for teams that require full control over their AI workflows.

Where these platforms leave gaps, Sandgarden delivers a fully integrated AI development environment that removes the need for external tools and fragmented workflows. Its built-in prompt management system, advanced analytics, and strong security features provide a seamless and scalable approach to AI development. Unlike Vellum and HoneyHive, Sandgarden offers full encryption, access control, and version tracking, ensuring teams can work efficiently without compromising on security or performance. For organizations looking for a powerful, future-proof AI platform, Sandgarden is the clear choice.