Vellum

Prompting: Systematically iterate on prompts

- Unified prompt management dashboard

- Side-by-side model comparisons

- Native support for tools, structured outputs, OpenAPI specs

Workflows: The IDE for building steerable, agent-like systems.

- Visual graph builder for orchestrating complex AI systems

- Support for any model, custom code, and map/reduce functions

- Built-in features like loops, parallelism, error handling

Workflows SDK: A full-stack SDK + GUI for building AI apps with precision and flexibility.

- Bi-directional sync between code and UI

- Fine-grained control flow and global state management

- Customizable with Docker and streaming support

Evaluations: Test-driven development for AI.

- Build scalable test suites via UI/API/CSV

- Use pre-built or custom metrics for evaluation

- Track quality, cost, latency, and regressions over time

Retrieval: Powerful RAG infrastructure without the complexity.

- Simple APIs for uploading and querying unstructured data

- Tweak chunking, embeddings, and search for advanced use-cases

- Supports various file types including tables and images

Deployments: Update AI systems without redeploying your app.

- One-click deploy across any model or provider

- Staging environments for safe iteration

- Scalable inference endpoints for production use

Observability: Full visibility into AI system performance.

- Audit logs, debugging tools, and feedback capture

- Evaluation loops on live traffic

- Dashboards to track cost, latency, errors, and trends

High-Level Overview

Vellum is an AI product development platform designed to enable teams—especially product managers, AI engineers, and startups—to rapidly prototype, test, and deploy AI-powered applications and workflows with minimal coding. Its core offering includes an intuitive Agent Builder that allows users to create and optimize AI workflows using natural language prompts, a visual low-code interface, and robust tools for evaluation, version control, and continuous improvement without full redeployment. Vellum serves companies building AI agents and LLM (large language model) applications, helping them overcome common bottlenecks in AI product development by streamlining experimentation, deployment, and iteration while maintaining high standards of quality, safety, and reliability[1][2][3][5].

For an investment firm, Vellum represents a key player in the AI development tools sector, focusing on accelerating AI product delivery and enabling broader adoption of generative AI technologies. Its impact on the startup ecosystem includes empowering smaller companies and cross-functional teams to build sophisticated AI features faster and more confidently, thus lowering barriers to AI innovation and fostering a more dynamic AI application market[6].

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Origin Story

Vellum was founded by Noa Flaherty, Akash Sharma, and Sidd Seethepalli, who brought together expertise in AI and software development to address the challenges of building complex AI workflows. The idea emerged from recognizing the difficulty companies face when trying to experiment with and productionize multi-step AI prompt chains and workflows, especially those involving semantic search and business logic integration. Early traction came from helping dozens of customers transition AI prototypes into production-ready applications by providing tools for efficient prompt engineering, versioning, and monitoring. Over time, Vellum evolved from a prompt engineering tool into a fully managed platform for deploying and managing AI workflows, reflecting the growing complexity and demand in the AI application space[4].

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Core Differentiators

• Natural Language Agent Builder: Enables creation and optimization of AI workflows in minutes using plain English, eliminating the need for extensive coding or drag-and-drop interfaces[1][3][5].
• Low-Code Visual Workflow Design: Allows users to visually adjust logic and package AI agents into reusable apps, making it accessible to non-engineers like product managers[3][4].
• Robust Evaluation and Version Control: Built-in testing, side-by-side comparison of prompt variants, safe rollbacks, and continuous monitoring ensure high-quality, reliable AI behavior before deployment[1][3][4].
• Seamless Integration and Deployment: Supports embedding AI agents via SDKs or APIs, with enterprise-grade security and flexible deployment options including on-premises and VPC[5].
• Collaborative Environment: Facilitates cross-functional teamwork with shared access to AI agents and workflows, accelerating iteration cycles and feedback loops[1][3].
• Provider Agnostic: Supports multiple AI models and providers, allowing users to test and switch between models like GPT-4 and Llama 2 without code changes[2].
• Continuous Improvement Without Downtime: Updates and improvements can be made without full application redeployment, reducing risk and accelerating iteration[1].

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Role in the Broader Tech Landscape

Vellum rides the wave of rapid adoption of generative AI and large language models by addressing a critical market need: simplifying the complex, error-prone process of building, testing, and deploying AI workflows at scale. As AI applications become more sophisticated and integrated into business processes, the timing for a platform like Vellum is ideal. Market forces such as the explosion of AI model availability, demand for faster time-to-market, and the need for reliable, maintainable AI systems favor platforms that reduce engineering overhead and risk. Vellum influences the ecosystem by democratizing AI development, enabling smaller teams and non-engineers to contribute to AI product innovation, and setting standards for AI workflow management and observability[1][2][4][6].

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Quick Take & Future Outlook

Looking ahead, Vellum is poised to expand its influence by deepening its platform capabilities around multi-step AI workflows, enhanced observability, and enterprise security. Trends such as increasing AI adoption across industries, demand for responsible AI deployment, and the proliferation of specialized AI models will shape its journey. Vellum’s ability to integrate seamlessly with evolving AI technologies and provide a low-code, collaborative environment positions it well to become a foundational tool for AI product development. Its future may include broader ecosystem partnerships, expanded AI model support, and further automation of AI lifecycle management, reinforcing its role as a critical enabler in the AI innovation landscape[4][6].

This trajectory ties back to Vellum’s core mission: to empower teams to build AI products faster, safer, and with greater confidence, transforming how AI-powered applications are created and scaled.