Vellum is a development platform for building, testing, and deploying applications powered by large language models. It brings together prompt engineering, workflow building, evaluation, and deployment into one environment so teams can move LLM features toward production with more structure. Users can design multi step workflows, compare prompts and models, run evaluations against test cases, and monitor how applications behave once live. Vellum supports multiple model providers and includes tools for versioning and collaboration, helping teams manage the experimentation and iteration that LLM development typically requires.
The platform is aimed at product teams, developers, and companies building LLM features who want reliable tooling around prompts and workflows rather than ad hoc scripts. It fits organizations creating chat assistants, retrieval based applications, and multi step AI workflows that need testing and quality control before release. Because it emphasizes evaluation and collaboration, it suits teams where product managers, engineers, and others work together on AI features. Its focus on the path from prototype to production makes it useful for companies treating LLM applications as maintained products rather than one off experiments.
In practice, teams craft prompts, assemble workflows, and run evaluations to compare outputs across models and versions. Approved workflows are deployed and exposed through APIs for use in applications. Monitoring and versioning help teams track performance, catch regressions, and iterate on their AI features over time.
