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Vellum

Use Vellum to build and ship reliable AI solutions. Define, evaluate and monitor AI solutions through test-driven development for AI.

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Founded

2023

Location

New York, New York

Employees

37

Funding

$25.5M

Vellum: Enterprise Platform for Building, Evaluating, and Operating AI Agents

Vellum is an enterprise-grade platform for designing, testing, deploying, and monitoring AI agents and LLM-powered applications. It unifies orchestration, evaluations, versioning, routing, and production observability so teams can ship reliable AI into real workflows—without stitching together disparate tools.

  • YC batch: **W23**
  • HQ: **New York, NY (Madison Ave)**
  • Ideal for: Product, engineering, data/platform, and operations teams building AI into production workflows with governance and compliance needs
  • Start free: See the **Free plan** on the [pricing page](https://www.vellum.ai/pricing)

    • Explore Vellum: [Homepage](https://www.vellum.ai/) | [Docs](https://docs.vellum.ai/home/getting-started/overview) | [LLM Leaderboard](https://www.vellum.ai/llm-leaderboard) | [Orchestration](https://www.vellum.ai/products/orchestration)

    ---

    Why Vellum

  • Build agents in plain English or as **visual workflows** with tools and function calling
  • Centralize **orchestration, evaluations, observability, routing, and versioning** in one platform
  • Integrate any model (OpenAI, Anthropic, Google, Azure OpenAI, open-source) and connect external systems via APIs and webhooks
  • Ship safely with **SOC 2 Type 2, HIPAA, SSO, RBAC, VPC/private networking**, audit logs, and governance
  • Improve quality over time with **evals, datasets, A/B testing, benchmarking**, and production traces

    • Learn more: [Orchestration & Agent Builder](https://www.vellum.ai/products/orchestration) | [Evaluations](https://www.vellum.ai/blog/introducing-vellum-evaluations) | [Levels of Agentic Behavior](https://www.vellum.ai/blog/levels-of-agentic-behavior)

    ---

    Key Capabilities

  • **Agent Builder**
  • Design agents by chatting in natural language or assembling **node-based visual workflows**
  • Add tool use via **function calls** and custom actions; connect to external APIs and webhooks
  • Mix and match **internal and external models**; enable routing by cost, quality, or latency
  • **Evaluations & Experimentation**
  • Run **evals** before rollout using datasets and benchmarks
  • **Compare prompts, models, and versions**; A/B test workflows to quantify improvements
  • Use the public [LLM Leaderboard](https://www.vellum.ai/llm-leaderboard) to compare models by benchmarks, cost, and context windows
  • **Production Observability**
  • End-to-end **tracing, logging, and feedback capture** for real-world monitoring
  • **Versioning and safe deployments:** promote/rollback versions with auditability
  • **Governance & Collaboration**
  • **SSO, RBAC, audit logs**, and private networking options
  • Share agents across teams; track changes and debug with **production traces**
  • **Deployment Options**
  • Ship via **API**, generate internal UIs with one click, or embed widgets

    • Get started: [Docs Overview](https://docs.vellum.ai/home/getting-started/overview)

    ---

    Security & Compliance

  • Certifications and controls: **SOC 2 Type 2**, **HIPAA**, **SSO**, **RBAC**, **VPC/private networking**, audit logs
  • Built for enterprises needing **governance, auditability, and controlled rollout**

    • Details: [Security features referenced across product pages](https://www.vellum.ai/)

    ---

    Who It’s For

  • **Product managers and engineers** shipping AI features into production
  • **Data and platform teams** standardizing LLM ops, governance, and observability
  • **Enterprise teams** in SaaS, healthcare, fintech, support, and operations requiring evals, auditability, and compliance

    • ---

    Common Use Cases

  • Customer support and internal assistants with tool use and retrieval
  • Sales enablement and content generation with approval steps
  • Knowledge assistants with **RAG** and guardrails
  • Operations automations that call internal APIs and back-office systems
  • **Evaluation pipelines** and A/B testing for prompts, models, and workflows
  • SEO and content workflows from research to publishing
  • Example: [Notion Article Generator Template](https://www.vellum.ai/template/generate-article-in-notion)

    • ---

    Integrations

  • Models: **OpenAI, Anthropic, Google, Azure OpenAI**, and **open-source models**
  • Data & memory: Retrieval over your data, vector stores, and in-product datasets
  • Tools & actions: Function calling, APIs, webhooks, SDK, and custom tools
  • Enterprise: **SSO, RBAC, audit logs, private networking**
  • Observability: Production tracing, logging, and feedback capture

    • More on orchestration and integrations: [Product Overview](https://www.vellum.ai/products/orchestration)

    ---

    Pricing

  • **Free plan available** to start building and testing
  • Usage-based and enterprise tiers for scale, governance, and advanced features

    • See details: [Pricing](https://www.vellum.ai/pricing)

    ---

    Customer Sentiment (Pros & Cons)

    Pros

  • Strong visual builder and collaboration—non-dev teammates can contribute to workflows

    • Source: [Reddit: r/AI_Agents](https://www.reddit.com/r/AI_Agents/comments/1nqyy1r/tried_a_bunch_of_aiagent_platforms_and_what/)

  • Workflows and function calling reduce custom code and save engineering time

    • Source: [G2 Reviews](https://www.g2.com/products/vellum/reviews)

  • Fast way to prototype, test, deploy, and observe LLM workflows in one place

    • Source: [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-skbe6ou2xiqc4)

  • Built-in evals and versioning support safer iteration and quality gates

    • Source: [G2 Pros & Cons](https://www.g2.com/products/vellum/reviews?qs=pros-and-cons)

  • Helpful, responsive support for complex setups

    • Source: [AWS Marketplace Reviews](https://aws.amazon.com/marketplace/reviews/reviews-list/prodview-skbe6ou2xiqc4)

    Cons

  • Advanced flows can feel complex without guidance

    • Source: [G2 Pros & Cons](https://www.g2.com/products/vellum/reviews?qs=pros-and-cons)

  • Pricing transparency has been a concern for some users

    • Source: [Reddit: r/ChatGPT](https://www.reddit.com/r/ChatGPT/comments/1fzny2e/how_much_does_vellumai_cost/)

  • Higher cost vs. DIY stacks, offset by time savings at scale

    • Source: [Reddit: r/AI_Agents](https://www.reddit.com/r/AI_Agents/comments/1nqyy1r/tried_a_bunch_of_aiagent_platforms_and_what/)

    ---

    Notable Resources

  • Product and positioning: [Homepage](https://www.vellum.ai/)
  • Orchestration and agent builder: [Product](https://www.vellum.ai/products/orchestration)
  • Evaluations: [Introducing Vellum Evaluations](https://www.vellum.ai/blog/introducing-vellum-evaluations)
  • Best practices: [Ultimate LLM Agent Build Guide](https://www.vellum.ai/blog/the-ultimate-llm-agent-build-guide)
  • Agent maturity: [Levels of Agentic Behavior](https://www.vellum.ai/blog/levels-of-agentic-behavior)
  • Model comparisons: [LLM Leaderboard](https://www.vellum.ai/llm-leaderboard)
  • Company updates: [LinkedIn](https://www.linkedin.com/company/vellumai)

    • ---

    Quick Facts

  • Company: **Vellum**
  • What it does: **Enterprise platform to build, evaluate, deploy, and monitor AI agents and LLM apps**
  • HQ: **New York, NY, USA**
  • Team size: ~37 (LinkedIn)
  • YC batch: **W23**
  • Funding: Seed and growth rounds; a **$20M raise** was shared on [LinkedIn](https://www.linkedin.com/company/vellumai)
  • Product pillars: **Orchestration, Evaluations, Observability, Versioning, Routing, Governance**
  • LLM Leaderboard: [Public comparison page](https://www.vellum.ai/llm-leaderboard)
  • Pricing: **Free plan** available; paid tiers on the [pricing page](https://www.vellum.ai/pricing)

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