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Testing & Quality🔴Developer
V

Vellum

LLM development platform for prompt engineering, evaluation, workflow orchestration, and deployment of production AI applications. Helps engineering teams build, test, and ship LLM-powered features with version control and observability.

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In Plain English

An LLM development platform that provides prompt engineering, evaluation, workflow building, and deployment tools for teams building production AI applications.

OverviewFeaturesPricingGetting StartedUse CasesLimitationsFAQAlternatives

Overview

Vellum is a freemium LLM development platform — free for up to 100,000 monthly prompt executions, with Pro plans starting at $89/seat/month — that helps engineering teams build, test, evaluate, and deploy production AI applications with confidence. Used by over 200 companies including teams at Fortune 500 enterprises, Vellum has processed more than 500 million LLM API calls through its platform and supports integration with 50+ foundation models across providers like OpenAI, Anthropic, Google, Cohere, and Meta.

The platform provides a complete toolkit spanning prompt engineering with side-by-side model comparison, automated evaluation pipelines for regression testing across prompt versions, a visual workflow builder for chaining LLM calls and agentic pipelines, and version-controlled deployment management with rollback capabilities. Vellum's evaluation framework has been used to run over 10 million automated test executions, helping teams catch regressions before they reach production.

Teams start in the prompt engineering playground, where they can compare outputs across models from multiple providers, iterating on prompts with full version history. Once prompts perform well in testing, Vellum's evaluation framework lets teams define quantitative test suites that automatically score outputs using custom metrics, LLM-as-judge configurations, or deterministic checks — catching regressions before they reach users.

The workflow builder enables teams to construct complex multi-step AI pipelines visually — chaining LLM calls, adding conditional logic, integrating tool use, and building retrieval-augmented generation (RAG) flows with document management and search indexes. Over 15,000 workflows have been deployed through the platform. These workflows deploy through Vellum's managed infrastructure with environment management (staging and production), A/B testing, and monitoring.

In production, Vellum provides observability into latency, cost, and quality metrics, giving teams visibility into how their AI features perform with real users. The platform integrates into existing CI/CD pipelines via REST API and SDKs for Python and TypeScript, with the Python SDK averaging over 50,000 weekly downloads on PyPI. Multi-user workspaces with role-based access control support collaboration across engineering teams of all sizes.

Vellum is SOC 2 Type II certified and offers HIPAA compliance on enterprise plans, making it suitable for regulated industries including healthcare and financial services. The platform does not train on customer data and acts as a passthrough to model providers, addressing common enterprise data privacy concerns.

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Key Features

Prompt Engineering Playground+

Vellum's playground lets teams compare prompt outputs across multiple LLM providers (OpenAI, Anthropic, Google, and others) side by side. Every prompt iteration is version-controlled, allowing teams to track changes over time and revert when needed. Variables and templates make it easy to test prompts against diverse inputs systematically rather than ad hoc.

Evaluation & Testing Framework+

The evaluation system allows teams to define test suites with quantitative scoring criteria, then automatically run these suites against prompt changes to catch regressions before deployment. This shifts LLM quality assurance from manual spot-checking to systematic, repeatable testing integrated into the development workflow.

Visual Workflow Builder+

Vellum's workflow builder provides a visual interface for constructing complex multi-step AI pipelines. Teams can chain LLM calls, add conditional branching logic, integrate external tool use, and build retrieval-augmented generation flows — all without writing orchestration code. Workflows can be deployed and versioned like prompts.

Deployment Management+

Prompts and workflows deploy through Vellum's managed infrastructure with environment separation (staging, production), rollback capabilities, and A/B testing support. This gives teams the same deployment safety practices they use for application code, applied to their AI components.

RAG & Document Management+

Vellum provides document upload, indexing, and search capabilities for teams building retrieval-augmented generation applications. Teams can manage their knowledge bases, configure search parameters, and test retrieval quality alongside prompt performance in a unified platform.

Pricing Plans

Free

$0

  • ✓100,000 monthly prompt executions
  • ✓Playground access with multi-model comparison
  • ✓Basic evaluation with up to 5 test suites
  • ✓1 workspace with up to 3 users
  • ✓Community support

Pro

From $89/seat/month

  • ✓500,000+ monthly prompt executions
  • ✓Advanced evaluation pipelines with unlimited test suites
  • ✓Full workflow builder access
  • ✓Priority email and chat support
  • ✓Team collaboration with multiple workspaces
  • ✓Production deployment management

Enterprise

Custom

  • ✓Unlimited prompt executions
  • ✓SSO/SAML authentication
  • ✓HIPAA compliance
  • ✓Dedicated support and SLA
  • ✓Custom data retention policies
  • ✓Advanced RBAC and audit logging
See Full Pricing →Free vs Paid →Is it worth it? →

Ready to get started with Vellum?

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Getting Started with Vellum

  1. 1Sign up for a free account at vellum.ai
  2. 2Create your first prompt in the playground and compare outputs across models
  3. 3Set up an evaluation test suite to establish a quality baseline
  4. 4Build a workflow to chain multiple LLM steps together
  5. 5Deploy a prompt to a staging environment and integrate via the API
  6. 6Monitor production performance through the observability dashboard
Ready to start? Try Vellum →

Best Use Cases

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Engineering teams building customer-facing AI chatbots or content generation features that need systematic prompt testing and safe deployment practices

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Organizations in regulated industries (healthcare, finance) requiring SOC 2 and HIPAA-compliant LLM infrastructure for production AI applications

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AI teams constructing complex RAG applications who need integrated document management, search tuning, and retrieval quality evaluation

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Product teams shipping AI features across multiple LLM providers who need model-agnostic orchestration and easy provider switching

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DevOps-minded AI teams wanting to bring CI/CD best practices — version control, automated testing, staged rollouts — to their prompt and workflow management

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Enterprises building multi-step agentic workflows that require visual orchestration, conditional logic, and tool integration without writing custom orchestration code

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Vellum doesn't handle well:

  • ⚠Platform acts as intermediary to LLM providers, adding a potential point of failure
  • ⚠Free tier has limited execution volume, requiring upgrade for production workloads
  • ⚠Enterprise features like HIPAA and SSO are gated behind custom pricing
  • ⚠Visual workflow builder may not cover every edge case that code-based orchestration handles
  • ⚠Evaluation scoring requires teams to invest upfront in defining quality metrics

Pros & Cons

✓ Pros

  • ✓Complete LLM development lifecycle in one platform — from prompt engineering through production monitoring
  • ✓Automated evaluation pipelines catch prompt regressions before they reach users
  • ✓Visual workflow builder enables complex AI pipelines without orchestration code
  • ✓Model-agnostic approach supports OpenAI, Anthropic, Google, and other providers side by side
  • ✓SOC 2 Type II certified with HIPAA compliance available for regulated industries
  • ✓Strong API and SDK support (Python, TypeScript) for CI/CD integration

✗ Cons

  • ✗Learning curve for teams new to structured LLM development practices
  • ✗Pro tier at $89/seat/month is higher than some competitors, and Enterprise requires custom sales engagement
  • ✗Adds a dependency layer between your application and LLM providers
  • ✗Workflow builder may be less flexible than code-first orchestration for very complex pipelines
  • ✗Evaluation framework effectiveness depends on teams defining good test criteria

Frequently Asked Questions

What is Vellum used for?+

Vellum is an LLM development platform used by engineering teams to build, test, evaluate, and deploy production AI applications. It provides prompt engineering tools, automated evaluation pipelines, a visual workflow builder, and deployment management with version control and monitoring.

Does Vellum support multiple LLM providers?+

Yes, Vellum is model-agnostic and supports major LLM providers including OpenAI, Anthropic, Google, and others. Teams can compare outputs across models side by side in the playground and switch providers in production without rebuilding application logic.

Does Vellum have an API?+

Yes, Vellum provides a REST API and SDKs for Python and TypeScript. The API allows teams to execute prompts and workflows programmatically, manage deployments, submit evaluation data, and integrate Vellum into CI/CD pipelines.

Is Vellum SOC 2 compliant?+

Yes, Vellum is SOC 2 Type II certified. Enterprise plans also offer HIPAA compliance, SSO/SAML authentication, and configurable data retention policies for regulated industries.

How does Vellum compare to LangSmith?+

Both platforms serve the LLMOps space but with different emphases. Vellum provides a more integrated prompt-to-deployment workflow with visual workflow building and managed deployment infrastructure. LangSmith, built by the LangChain team, focuses more on tracing and observability for LangChain-based applications. The best choice depends on your existing tech stack and whether you prioritize visual workflow building or deep LangChain integration.

Is there a free tier for Vellum?+

Yes, Vellum offers a free tier that includes 100,000 monthly prompt executions, playground access with multi-model comparison, basic evaluation with up to 5 test suites, and support for up to 3 users. The Pro tier starts at $89/seat/month for teams needing higher limits and advanced features, while Enterprise plans with HIPAA compliance and SSO are custom-priced.
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What's New in 2026

Vellum continues to develop its LLM development platform with enhancements to the workflow builder, evaluation framework, and deployment management capabilities. The platform supports the latest models from major providers and has expanded its enterprise compliance and security features.

Alternatives to Vellum

LangSmith

Analytics & Monitoring

LangSmith lets you trace, analyze, and evaluate LLM applications and agents with deep observability into every model call, chain step, and tool invocation.

Humanloop

Analytics & Monitoring

Former LLMOps platform for prompt engineering and evaluation, acquired by Anthropic in August 2025. Technology now integrated into Anthropic Console as the Workbench and Evaluations features.

Braintrust

Voice Agents

AI observability platform with Loop agent that automatically generates better prompts, scorers, and datasets from production data. Free tier available, Pro at $25/seat/month.

Portkey AI

Analytics & Monitoring

AI gateway and observability platform for managing multiple LLM providers with routing, fallbacks, and cost optimization.

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Quick Info

Category

Testing & Quality

Website

vellum.ai
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