Vellum AI

Vellum is a production platform for LLM applications that addresses the workflow challenges between prototyping an AI feature and running it reliably at scale. The gap between a working prompt in ChatGPT and a production-grade LLM pipeline is substantial, and Vellum provides tooling for the testing, evaluation, and deployment steps that this transition requires.

The prompt management feature allows teams to iterate on prompts without code deployments — changing a prompt, testing it against a dataset, comparing it to the previous version, and deploying the winner happens within Vellum rather than requiring engineering tickets and deployments. For product teams that want to adjust AI behaviour frequently, this operational flexibility is significant.

Evaluation and regression testing are core to Vellum's value proposition. As prompts change or models update, Vellum runs the new configuration against curated test datasets and compares performance. This catches regressions before they affect users, which is critical for applications where AI response quality is a product differentiator.

Workflow orchestration allows building multi-step LLM pipelines visually — connecting retrieval, processing, and generation steps into deployable endpoints. The visual pipeline builder reduces the code required for common AI application patterns.

Vellum competes with LangSmith and Langfuse on observability and evaluation, but differentiates with stronger focus on the full deployment workflow including prompt versioning and no-code pipeline building. Teams that want a more complete AI application platform rather than a pure observability layer will find Vellum a useful complement or alternative.