Vellum AI

aid: vellum
name: Vellum AI
description: >-
  Vellum AI is an LLM development platform that helps product and engineering
  teams build, evaluate, deploy, and monitor LLM-powered applications. The
  platform centers on prompt engineering, a visual Workflows builder for
  agentic and multi-step pipelines, evaluation suites with dataset
  management, retrieval-augmented generation, and production observability
  with logs, traces, and metrics. Target customers are AI product teams at
  startups and enterprises that need version control, collaboration, and
  vendor-neutral access across OpenAI, Anthropic, Google, Mistral, and open
  models. Vellum exposes a REST API plus Python and TypeScript SDKs, runs in
  cloud and self-hosted deployments, and offers tiered pricing for
  Pro/Business/Enterprise. Note: as of 2026 the vellum.ai marketing surface
  has been refocused on a personal AI assistant product; the developer
  platform documented here remains the LLM application stack.
type: Index
position: Provider
access: 3rd-Party
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
  - LLM Platform
  - Prompt Engineering
  - Workflows
  - Evaluations
  - LLM Ops
  - RAG
  - Observability
  - Datasets
  - Deployments
  - Multi-Provider
  - Agent Builder
  - Self-Hosted
url: https://raw.githubusercontent.com/api-evangelist/vellum/refs/heads/main/apis.yml
created: '2026-05-23'
modified: '2026-05-23'
specificationVersion: '0.20'
apis:
  - aid: vellum:llm-platform
    name: Vellum LLM Platform API
    description: >-
      The Vellum REST API exposes prompts, workflows, evaluations, datasets,
      document indexes, deployments, and execution endpoints so developers can
      run versioned LLM pipelines from their own backends and capture logs and
      metrics for production monitoring.
    humanURL: https://docs.vellum.ai
    baseURL: https://api.vellum.ai
    tags:
      - Prompts
      - Workflows
      - Evaluations
      - Datasets
      - Documents
      - Deployments
      - Executions
      - Monitoring
    properties:
      - type: Documentation
        url: https://docs.vellum.ai
      - type: APIReference
        url: https://docs.vellum.ai/api-reference
      - type: GettingStarted
        url: https://docs.vellum.ai/welcome/getting-started
      - type: SignUp
        url: https://app.vellum.ai/signup
      - type: SDK
        url: https://github.com/vellum-ai/vellum-client-python
      - type: SDK
        url: https://github.com/vellum-ai/vellum-client-typescript
      - type: GitHubOrganization
        url: https://github.com/vellum-ai
      - type: Pricing
        url: https://www.vellum.ai/pricing
      - type: Blog
        url: https://www.vellum.ai/blog
    features:
      - name: Prompt Engineering Workbench
        description: Versioned prompts, side-by-side model comparisons, and structured prompt variables.
      - name: Workflows Builder
        description: Visual builder for multi-step LLM pipelines including branching, tools, and RAG nodes.
      - name: Evaluation Suites
        description: Run dataset-driven evals with built-in and custom metrics for prompts and workflows.
      - name: Dataset Management
        description: Store labeled test cases and production examples to drive evaluations and fine-tuning.
      - name: Document Indexes / RAG
        description: Managed document ingestion, embeddings, and retrieval for grounded generation.
      - name: Deployments and Versioning
        description: Promote prompts and workflows through environments with rollback and traffic splits.
      - name: Production Monitoring
        description: Logs, traces, latency, cost, and quality metrics for every execution.
      - name: Multi-Provider Routing
        description: Vendor-neutral access to OpenAI, Anthropic, Google, Mistral, and open models.
      - name: SDKs for Python and TypeScript
        description: First-class SDKs for invoking prompts, workflows, and datasets from application code.
      - name: Self-Hosted Option
        description: Deploy Vellum into the customer's own cloud for compliance-sensitive workloads.
    useCases:
      - name: Build Production LLM Apps
        description: Iterate on prompts and workflows, then deploy versioned endpoints into apps.
      - name: Evaluate LLM Quality
        description: Use datasets and evals to measure regressions across models and prompt variants.
      - name: Build Agents
        description: Compose tools, retrieval, and conditional logic via the visual workflow builder.
      - name: RAG Pipelines
        description: Ingest documents, index them, and query through Vellum's managed retrieval layer.
      - name: Observe and Debug
        description: Trace production runs to debug failures and improve quality over time.
    integrations:
      - name: OpenAI
      - name: Anthropic
      - name: Google
      - name: Mistral
      - name: Cohere
      - name: AWS Bedrock
      - name: Azure OpenAI
      - name: Pinecone
      - name: Snowflake
      - name: LangChain
      - name: LlamaIndex
    authentication:
      - type: API Key
        description: Workspace API keys passed via the `X_API_KEY` header authenticate REST and SDK calls.
common:
  - type: Website
    url: https://www.vellum.ai
  - type: Documentation
    url: https://docs.vellum.ai
  - type: Blog
    url: https://www.vellum.ai/blog
  - type: GitHubOrganization
    url: https://github.com/vellum-ai
  - type: Pricing
    url: https://www.vellum.ai/pricing
  - type: SignUp
    url: https://app.vellum.ai/signup
  - type: Login
    url: https://app.vellum.ai/login
  - type: TermsOfService
    url: https://www.vellum.ai/terms-of-service
  - type: PrivacyPolicy
    url: https://www.vellum.ai/privacy-policy
  - type: Twitter
    url: https://x.com/vellum_ai
  - type: LinkedIn
    url: https://www.linkedin.com/company/vellum-ai
maintainers:
  - FN: Kin Lane
    email: [email protected]