Vellum AI vs Gumloop: Full Comparison

Who to consider instead of Vellum (as of July 2026)

If you were evaluating Vellum for a business AI workflow use case, the platforms still in that market are:

• Gumloop - no-code visual builder, business-user focused, still independent (see comparison below).
• Relay.app - workflow-first, human-in-the-loop approvals, independent.
• n8n - open-core, technical, now with SAP investment and a licence deal for SAP integration.
• Lindy - agent-focused, independent.
• Agent Console HQ - independent by design, not backed by a suite vendor, not steering towards acquisition. Full disclosure: this site's parent company.

If you were evaluating Vellum specifically for LLM operations (prompt management, evaluation, deployment), rather than workflow automation, the alternatives are different: LangSmith, Braintrust, Humanloop, PromptLayer. Vellum's LLM ops functionality may still be reachable via legacy docs for existing customers, but it is no longer their marketed product.

The Core Difference (as of early 2026)

Vellum AI was a developer-focused LLMOps platform (as of early 2026, before its June 2026 pivot to a personal AI assistant). It had strong prompt management, evaluation tooling, and versioning for production AI deployments inside a product.

Gumloop is a visual no-code workflow builder. Business users can build AI automations on a canvas without code.

Vellum was a tool for engineers, as of early 2026. Gumloop is a tool for everyone else.

Vellum AI Strengths (as of early 2026)

These strengths described Vellum's enterprise LLMOps product before its June 2026 pivot. They no longer reflect Vellum's current, personal-assistant-focused product.

Prompt management: first-class tooling for iterating, versioning, and comparing prompts.

Evaluation: built-in eval framework for measuring prompt quality.

Deployment: production-grade prompt and workflow deployments with rollback.

Developer experience: strong SDK, good docs, API-first approach.

Observability: tracing and logging for production AI.

Gumloop Strengths

Visual builder: drag-and-drop canvas that non-developers can use.

Templates: rich library of starting workflows.

AI-native: designed specifically for LLM workflows, not general automation.

Speed: ship your first working workflow in under an hour.

Collaboration: marketing, sales, and ops teams can all contribute.

Pricing (as of early 2026)

Vellum (as of early 2026): from around $500/month. Enterprise pricing available. Pricing under Vellum's new personal AI product line is different.

Gumloop: from $97/month. Scales with execution volume.

Vellum was much more expensive but targeted a different buyer, as of early 2026: teams embedding AI into their own products.

Who Should Pick Vellum (as of early 2026)

You are building a product that uses LLMs and need production-grade prompt management.

Your team is technical: engineers, ML engineers, product managers comfortable with APIs.

You need evaluation tooling to measure and improve prompt quality.

You have a significant budget and need enterprise features.

Note: as of July 2026 this recommendation no longer applies. Vellum has pivoted out of this market. See alternatives above.

Who Should Pick Gumloop

Your team is non-technical: marketing, sales, operations, founders without engineering support.

You want to automate internal workflows, not embed AI into a product.

You need results fast and cannot wait for engineering.

Your budget is mid-market, not enterprise.

Could You Use Both? (as of early 2026)

As of early 2026, some teams did. Gumloop for business workflows that the marketing team runs, Vellum for the LLM features embedded in your SaaS product. That pairing is no longer available now Vellum has left the business AI workflow market.

They were not competitors in the strict sense. They solved different problems for different users.