Vellum AI

Vellum AI is a comprehensive, enterprise-grade platform designed to streamline the entire lifecycle of developing generative AI applications. It serves as the backend for your AI products, empowering teams of engineers, product managers, and domain experts to collaborate effectively and build mission-critical AI agents with confidence. Vellum's all-in-one solution addresses the key challenges in AI development, from initial experimentation to production monitoring, ensuring reliability, quality, and speed.

The platform is built around a core philosophy of bringing rigor and structure to AI development. It allows teams to move beyond the 'black box' nature of AI by providing tools for quantitative measurement, reproducible workflows, and full visibility into production systems. Trusted by leading product-led companies and global enterprises, Vellum has proven to significantly accelerate development cycles and improve the quality of AI-powered features.

How to use Vellum AI

The development process on Vellum follows a structured, iterative lifecycle:

1. Experiment & Orchestrate: Begin by building your AI's business logic using Vellum's visual Workflow builder or its powerful SDK (Python/TypeScript). You can chain together various nodes, including Prompts, Tool calls, Retrieval-Augmented Generation (RAG) from your documents, and even custom code executed in Python or Docker containers. This allows for creating complex agentic systems with loops, recursion, and parallel branches.
2. Evaluate: Once a workflow is designed, you must rigorously test it. Vellum provides a comprehensive evaluation suite. Create test cases (or use the synthetic test case generator) to measure your AI's performance across key metrics like quality, cost, latency, and reliability. Compare different prompt versions or workflow structures side-by-side to find the optimal configuration.
3. Deploy: After reaching your desired performance threshold, deploy your AI workflow with confidence. Vellum's native release management and environment system (e.g., development, staging, production) decouples AI updates from your main application release cycle. This means you can push fixes and improvements to your AI instantly without a full code deploy.
4. Monitor: Post-deployment, maintain complete visibility into your AI's performance in production. Use Vellum's trace and graph views to understand every step of an execution. The monitoring dashboard helps you track key metrics, identify edge cases, and gather data for the next iteration, ensuring your AI remains reliable and effective over time.

Core Features of Vellum AI

• Workflow Orchestration: A visual, no-code/low-code builder and a full-featured SDK for defining complex AI logic. Supports custom Python/TypeScript nodes, custom Docker images, and built-in tool calling.
• Prompt Engineering Suite: An advanced editor for creating and managing prompts, including support for images and function calling. Features include version history, comparison mode, and a prompt optimizer.
• Retrieval-Augmented Generation (RAG): End-to-end system for RAG, including managed document ingestion, chunking, embedding, and hybrid search (semantic, keyword, rule-based).
• Comprehensive Evaluation: Measure performance with out-of-the-box metrics, custom Python-defined metrics, and LLM-based evaluations. Compare draft and deployed versions easily.
• Deployment & Release Management: Safely promote AI workflows through different environments (dev, staging, prod). Decouple AI logic updates from application releases.
• Production Monitoring: Full observability with trace-span and graph views, online evaluation dashboards, and integrations with tools like Datadog.
• Enterprise-Ready Security: SOC 2 Type II compliant, supports HIPAA BAA, offers VPC deployments, Single Sign-On (SSO), and Role-Based Access Controls (RBAC).
• Team Collaboration: A unified platform where engineers, PMs, and domain experts can collaborate, with changes synced between the UI and SDK.

Use Cases for Vellum AI

Vellum is versatile and powers a wide range of sophisticated AI applications:

• Automated Document Analysis: As demonstrated by GravityStack, Vellum can power agentic AI to review complex legal documents like credit agreements, cutting review time significantly.
• Enterprise-Grade Virtual Assistants: Companies like Redfin use Vellum to build, evaluate, and confidently launch customer-facing virtual assistants in multiple markets.
• Healthcare AI Solutions: DeepScribe and RelyHealth leverage Vellum to build clinician-trusted, HIPAA-compliant AI tools for tasks like medical scribing and deploying healthcare solutions, accelerating iteration and deployment.
• Internal Compliance & Automation: Drata built its enterprise-grade internal AI solution on Vellum, showcasing its capability for creating robust, secure internal tools.
• High-Scale Production Workflows: Revamp runs over 15 million LLM executions in production through Vellum, proving its scalability and reliability for high-throughput use cases.
• Personalized Customer Experiences: Glowing uses Vellum to create personalized AI-driven experiences in the hospitality industry.

Advantages of Vellum AI

Vellum provides a distinct competitive edge for teams building with AI:

• Accelerated Development: The unified platform and collaborative tools can speed up AI development by up to 10x.
• Increased Reliability: Rigorous, quantitative evaluation and robust monitoring ensure that AI applications are not just functional but mission-critical and trustworthy.
• Seamless Collaboration: Bridges the gap between technical and non-technical stakeholders, allowing for faster iteration and better product outcomes.
• Agile Deployment: Decoupling AI updates from code releases allows teams to respond instantly to issues or opportunities without waiting for the next deployment cycle.
• Scalability and Security: Built from the ground up for enterprise needs, offering the security, compliance, and scalability required for large-scale, sensitive applications.

Pricing and Plans

Vellum offers tailored plans to fit different team sizes and needs:

• Startup Plan: Designed for teams looking to build robust AI applications. This plan is available to start for free and includes core features like Prompt Engineering, Workflows (UI & SDK), Document Retrieval, Evaluations, Deployments, and Monitoring for up to 5 users.
• Enterprise Plan: Aimed at larger companies with custom requirements and a need for elevated support. This plan includes all features from the Startup plan, plus Role-Based Access Control (RBAC), multiple workspaces, VPC installation options, external monitoring integrations, Single Sign-On (SSO), custom contracts (including BAA/DPA), and dedicated enterprise support with SLAs. Pricing is custom and available upon booking a demo.