Vellum AI is an LLM development platform that allows product and developer teams to create complex AI applications without code redeployment. It combines a visual workflow editor, prompt engineering tools, systematic evaluation and model management. Compatible with OpenAI, Anthropic, Google and Cohere, Vellum allows testing agents in staging before production, collaborating as a team and ensuring SOC 2 Type II and HIPAA compliance. Its free plan includes 50 builder credits per month to get started without commitment.
What is Vellum AI?
The essentials
Vellum AI is an orchestration and LLM development platform designed for technical teams. It allows you to create complex AI workflows using a visual editor where each node can represent an LLM call, Python or TypeScript code execution, a map/reduce operation or external API integration. Workflows can be tested in a staging environment before being deployed to production. Vellum also includes a prompt manager to version and compare prompt variations, as well as an evaluation suite to measure LLM output quality according to predefined or custom metrics.
Key features
Vellum offers a visual workflow editor to build LLM applications without modifying source code. Available nodes cover LLM model calls, arbitrary code execution, conditional operations, API integrations and documentary knowledge via a base of 20 documents on the free plan. Prompt engineering benefits from a dedicated editor with comparison modes, function calling support and multi-turn conversations. The evaluation suite offers out-of-the-box metrics, LLM-based evaluations and custom metrics in Python or TypeScript. Multi-environment management (staging, production) and version control facilitate deployment cycles. Business and Enterprise plans add multi-user collaboration with role-based access control, dedicated Slack support and compliance certifications.
Use cases
Vellum is particularly suited for teams developing advanced chatbots, automated content generation pipelines, document research agents or question-answering systems on proprietary data. Product teams use it to test prompt variations and measure their impact on answer quality without engaging developers. Healthcare and financial companies adopt it for its compliance guarantees. AI startups choose it to accelerate product development cycles by having an evaluation infrastructure from the start.
Advantages
Vellum significantly reduces the time needed to go from prototype to production LLM application. The visual editor allows iterating on workflows without touching code, freeing developers for higher value-add tasks. The automated evaluation suite reduces regression risk when updating models or prompts. Multi-vendor compatibility allows easy switching between models based on performance and costs. SOC 2 and HIPAA compliance remove barriers to adoption in regulated sectors.
Pricing
Vellum offers a free plan with 50 builder credits per month, one user, hosted agent applications, debug console and 20-document knowledge base. Access is possible without a credit card. Paid plans start at $25/month and include more credits, multiple users and advanced collaboration features. Business and Enterprise plans add role-based access control, separate staging/production environments and dedicated support levels. Enterprise plans include custom credit bundles, dedicated server sizing, Slack support and DPA/BAA contracts.
Conclusion
Vellum AI stands as a reference platform for teams taking seriously the development of LLM applications in production. Its combination of visual editor, rigorous evaluation and regulatory compliance makes it a solid choice for any ambitious AI project. For technical teams seeking to industrialize their AI workflows, Vellum represents a structural investment.