Vellum
AI workflow orchestration and evaluation platform for LLM apps.
What is Vellum?
Vellum is an AI tool in the AI Agent Builder Tools category. AI workflow orchestration and evaluation platform for LLM apps. AI-native builders for multi-step business agents and conversational workflows.
Teams typically bring in a tool like Vellum when a broader platform's built-in version of this workflow isn't specific enough for what they need, rather than as a wholesale replacement for their existing stack — it gets adopted as a focused point solution and plugged in alongside whatever CRM, data, or workflow tools a team already runs. Concretely, that means workspace for prompt engineering with side-by-side A/B testing of prompt versions, and workflow builder for chaining multiple LLM calls together. Whether it's the right point solution for your setup is worth checking directly — for current plans, limits, and integration details, see Vellum's own site; we'd rather point you there than guess.
Key Features
- Workspace for prompt engineering with side-by-side A/B testing of prompt versions
- Workflow builder for chaining multiple LLM calls together
- Evaluation suite runs regression tests against saved test cases before deploying prompt changes
Where Vellum fits in your stack
Vellum usually sits alongside the rest of a team's agent builder stack rather than replacing it outright. In our directory it's grouped with Lindy, Voiceflow, Relevance AI — if you're evaluating Vellum, you're most likely comparing it against one of those, since they cover the same job, not a tool from an unrelated category. The ceiling most teams hit with tools in this category isn't the tool itself — it's the point where the workflow needs logic a vendor UI can't express (see the callout below).
Where a point solution like Vellum breaks
- Agent builders give you a flow diagram — real multi-step reasoning with error recovery usually needs custom logic outside the builder
- Connecting an agent to a proprietary internal system is often unsupported without custom code anyway
- Debugging why an agent made a specific decision is hard when the logic lives in a visual builder instead of readable code
No-code agent builders are a fast way to prototype. An embedded engineer builds the same class of agent as maintainable, debuggable code connected to your actual internal systems, not just the ones the builder pre-integrated. See the sidebar to talk it through.
Vellum alternatives
Other ai agent builder tools in our directory.
Lindy
AI agent builder for automating multi-step business workflows.
Voiceflow
No-code builder for AI conversational agents and voice apps.
Relevance AI
Platform for building and deploying custom AI agents for business workflows.
CrewAI
Open-source framework for orchestrating multi-agent AI workflows.
Not a tool — an embedded engineer
No-code agent builders are a fast way to prototype. An embedded engineer builds the same class of agent as maintainable, debuggable code connected to your actual internal systems, not just the ones the builder pre-integrated. See the sidebar.
Frequently asked questions
AI workflow orchestration and evaluation platform for LLM apps. Specifically: workspace for prompt engineering with side-by-side A/B testing of prompt versions; workflow builder for chaining multiple LLM calls together; evaluation suite runs regression tests against saved test cases before deploying prompt changes. It's categorized in our directory under AI Agent Builder Tools.