For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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  • Getting Started
    • Overview
  • Agent Builder
    • Using the Agent Builder
  • Prompts
    • Prompt Engineering
    • Collaboration
    • Custom Models
    • Multimodality
    • Prompt Caching
  • Workflows
    • Introduction
    • Experimenting
    • Integrating
    • Function Calling
  • Evaluation & Test Suites
    • Quantitative Evaluation
    • Evaluating RAG Pipelines
    • Online Evaluations
  • Metrics
    • Out of the Box Metrics
    • Custom Metrics
    • Reusing Metrics in Test Suites
  • Deployments
    • Deployment Lifecycle Management
    • Observability in Production
    • Environments
    • Release Tags
    • Release Reviews
  • Monitoring
    • Monitoring Production Trends
    • Track Workflow Execution Costs
    • Datadog Integration
    • Webhook Integration
    • Execution URLs
  • Documents
    • Uploading Documents
    • Integrating w/ Search API
    • Metadata Filtering
  • Security
    • Data Privacy and Storage
    • HMAC Authentication
    • Role-Based Access Control (RBAC)
    • Static IPs
  • Organizations
    • Manage Organization Access
    • Data Retention Policies
  • Overview
  • Using the Agent Builder
  • Prompt Engineering
  • Collaboration
  • Custom Models
  • Multimodality
  • Prompt Caching
  • Introduction
  • Experimenting
  • Building a RAG Chatbot
  • Overview
  • Agent Node
  • Prompt Node
  • Prompt Deployment Node
  • Templating Node
  • Search Node
  • API Node
  • Code Execution Node
  • Subworkflow Node
  • Map Node
  • Guardrail Node
  • Conditional Node
  • Merge Node
  • Final Output Node
  • Error Node
  • Note Node
  • Node Adornments
  • Integrating
  • Overview
  • RAG System
  • Escalation to a Human
  • Prompt Retry Logic
  • PDF Content Summarization
  • Fallback Models
  • Function Calling
  • Long Running Workflows
  • Batching Executions
  • Static IPs
  • Overview
  • Prompt Chain
  • RAG Chatbot
  • RAG with Cohere Rerank
  • Customer Support Bot
  • Convert PDF to CSV
  • Summarize Images of Websites
  • Parallelized Function Calls
  • Lookup Conference Attendees
  • Multi-Agent Content Creation
  • LLMs Debating Each Other
  • Zapier Airtable Integration
  • Automating PR Reviews
  • Quantitative Evaluation
  • Evaluating RAG Pipelines
  • Online Evaluations
  • Out of the Box Metrics
  • Custom Metrics
  • Reusing Metrics in Test Suites
  • Deployment Lifecycle Management
  • Observability in Production
  • Environments
  • Release Tags
  • Release Reviews
  • Monitoring Production Trends
  • Track Workflow Execution Costs
  • Datadog Integration
  • Webhook Integration
  • Execution URLs
  • Uploading Documents
  • Integrating w/ Search API
  • Metadata Filtering
  • Data Privacy and Storage
  • HMAC Authentication
  • Role-Based Access Control (RBAC)
  • Static IPs
  • Manage Organization Access
  • Data Retention Policies
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On this page
  • Feature Documentation
  • Build
  • Test & Deploy
Getting Started

Welcome to Vellum

Welcome 👋 Vellum helps you to take AI products from early-stage idea to production-grade feature with tooling for experimentation, evaluation, deployment, monitoring, and collaboration.

Here you’ll find resources and guides for using the Vellum platform. Please don’t hesitate to contact us if you can’t find what you’re looking for.

Feature Documentation

Build

Prompt Engineering
Define and iterate on prompts across all open and closed source models
Workflows
Build advanced AI systems like agents, chatbots, data extraction pipelines
Common Architectures
Example workflows to help you get started
Document Search & RAG
Implement semantic search and RAG pipelines

Test & Deploy

Testing & Evaluation
Evaluate the quality of your AI systems at scale
Metrics
Choose metrics to evaluate your AI systems
Deployment
Version control and deploy your AI applications
Monitoring
Track performance and usage metrics
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Using the Agent Builder

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