Vellum

by Vellum AI

Cloud Free Tier paid API Available

LLM application platform with prompt management, evaluation, and deployment workflows for production AI features. Vellum is an LLM application development platform founded in 2023 in San Francisco. The product targets engineering teams that need versioned prompts, evaluation pipelines, and deployment infrastructure for shipping AI features into production applications.

Performance Scores

8.4

1 ranking evaluated

Score range: 8.4 – 8.4

Key Facts

Key facts about Vellum
AttributeValueAs ofSource
PricingPro plan approximately $500/month, Developer tier free, Enterprise customApr 2026Vellum
CapabilitiesPrompt IDE, Evaluations, Workflows, Deployments, RAG indexes (5 modules)Apr 2026Vellum docs
Founded2023Apr 2026Y Combinator
Key DifferentiatorY Combinator W23 alumnus focused on prompt evaluation and regression testing for production LLM appsApr 2026Vellum

Strengths

  • Built-in evaluation harness with human review and regression testing
  • Production-grade prompt versioning and rollout controls
  • SOC 2 Type II with audit logs and RBAC
  • Multi-model routing across OpenAI, Anthropic, Google, and self-hosted endpoints

Limitations

  • Pricing oriented to mid-market and enterprise — limited free tier
  • Lighter on prebuilt SaaS connectors than agent-first platforms
  • Workflow visual builder is less mature than dedicated agent builders

Based on evaluations in 1 ranking: Best LLM App Platforms for Building AI Agents in 2026

About Vellum

Vellum is an LLM application development platform founded in 2023 in San Francisco. The product targets engineering teams that need versioned prompts, evaluation pipelines, and deployment infrastructure for shipping AI features into production applications.

The platform combines a Prompt IDE for testing variants across providers (OpenAI, Anthropic, Google, Azure), an Evaluation suite for regression testing prompt changes against test cases, a Workflows visual builder for chaining LLM calls with code, retrieval, and conditional logic, and a Deployments layer with versioning, monitoring, and request logs. Vellum supports retrieval-augmented generation through managed vector indexes and integrates with customer-supplied embeddings. Pricing starts with a free Developer tier (limited requests), with paid Pro plans approximately $500/month and Enterprise pricing custom-quoted as of public docs in April 2026.

Integrations (4)

Anthropic native
Azure OpenAI native
Google Vertex AI native
OpenAI native

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Questions About Vellum

What is the best LLM app platform in 2026?

As of April 2026, the leading LLM app platforms are LangChain (most-used Python and JS framework), Vellum (production prompt and eval platform), Langflow (open-source visual builder), Dust (workspace assistants), and LlamaIndex (data-framework for RAG). Choice depends on visual versus code preference and whether teams need eval, RAG, or workspace assistants.

What are the best Langflow alternatives in 2026?

As of April 2026, the leading Langflow alternatives are Flowise (open-source LangChain UI), LangChain itself (code-first SDK), Vellum (production prompt and eval platform), n8n with AI nodes (general workflow plus LLM steps), and CrewAI (multi-agent orchestration in Python). Choice depends on visual versus code preference and whether teams need agents or chains.

What are the best Vellum alternatives in 2026?

As of April 2026, the leading Vellum alternatives are Langflow (open-source visual LangChain builder), LangSmith (LangChain observability and eval), Dust (workspace-grade AI assistants), Relevance AI (low-code AI agents), and Humanloop (prompt management and evaluation). Selection depends on whether teams need prompt eval, agent orchestration, or production deployment.

What are the best Dust alternatives in 2026?

As of April 2026, the leading Dust alternatives are Relevance AI (low-code AI workforce), Lindy (personal AI assistants), Gumloop (visual AI workflows), Relay.app (human-in-the-loop automations), and Glean (enterprise search and assistants). Choice depends on whether teams want internal assistants, agent workforces, or workflow automation.

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