Vellam

Personal AI that works for you

πŸ€– πŸ€– Chatbots & GPTs
⭐ 4.7 Rating
🏒 Vellum AI

πŸ“‹ About Vellam

Vellum is an AI product development platform designed to help engineering and product teams build, test, and deploy large language model (LLM) powered applications with greater confidence and speed. The platform was built by the Vellum team, co-founded by Nate Sesti and other AI-focused engineers, and launched in 2023 to address the growing complexity of taking LLM applications from prototype to production. It targets companies that need more than just an API connection β€” teams that require systematic workflows for prompt management, evaluation, and deployment.

The technology behind Vellum works by giving you a structured environment where you can design and chain together LLM workflows using a visual node-based editor, connect to models from providers like OpenAI, Anthropic, and Cohere, and run those pipelines against real data. You can version your prompts, test variations against regression suites, and track quality metrics over time without writing custom evaluation infrastructure from scratch. Vellum abstracts away much of the orchestration complexity while still giving developers direct control over model parameters, context windows, and decision logic at each step.

Among Vellum's standout features, its Prompt Sandbox lets you run side-by-side comparisons of different prompts and models, scoring outputs against custom criteria so you can make data-driven decisions before shipping. Its Test Suites feature allows you to define evaluation datasets and automatically check new prompt or model changes against historical performance benchmarks, catching regressions before they reach production. Additionally, Vellum's Document Indexes provide a managed vector store so you can build retrieval-augmented generation (RAG) pipelines directly within the platform without needing to set up and maintain a separate vector database.

Vellum operates on a freemium model, offering a free tier that gives smaller teams and individual developers access to core prompt management and sandbox features with limited usage. Paid plans start at the Starter and Growth tiers, which unlock higher API call volumes, team collaboration features, advanced evaluations, and priority support, making them suited for startups scaling their LLM products. Enterprise plans offer custom pricing, dedicated infrastructure, SSO, and compliance features for larger organizations with strict security and data governance requirements.

By 2026, Vellum has become a trusted tool among AI product teams at Series A through Series C startups as well as enterprise innovation labs that need to move fast without sacrificing reliability. You can find it used by teams building customer support bots, document processing pipelines, and intelligent search experiences, where consistent output quality directly affects user satisfaction. Companies report measurably shorter iteration cycles on prompt engineering and fewer costly model-related incidents in production, making Vellum a core part of the modern AI development stack.

⚑ Key Features

βœ“
Vellum enables teams to build, test, and deploy LLM-powered workflows with a visual no-code editor.
βœ“
Prompt versioning allows developers to track, compare, and roll back prompt changes across different model configurations.
βœ“
Vellum's evaluation suite lets users run systematic tests to measure LLM output quality and regression performance.
βœ“
Document search and retrieval features enable semantic search over custom knowledge bases for RAG pipelines.
βœ“
Teams can deploy prompts and chains to production with a single click, reducing engineering overhead significantly.
βœ“
Vellum provides detailed observability and logging so users can monitor real-time LLM usage and costs effectively.
βœ“
Collaboration tools allow product managers and engineers to work together on prompt iteration without code changes.
βœ“
Vellum supports multiple LLM providers including OpenAI, Anthropic, and Cohere so teams avoid vendor lock-in.

🎯 Popular Use Cases

πŸ”
LLM Prompt Engineering
Developers and AI engineers use Vellum to build, test, and iterate on prompts across multiple LLM providers in a structured environment. They achieve faster prompt optimization and consistent output quality without switching between tools.
πŸ“
AI Workflow Automation
Product teams use Vellum to design and deploy multi-step AI workflows with conditional logic and chaining capabilities. This enables them to automate complex document processing and customer interaction pipelines with measurable reliability.
πŸ“Š
LLM Performance Monitoring
Data scientists and ML engineers use Vellum's observability features to track latency, cost, and output quality of their deployed LLM applications. They gain actionable insights to optimize model selection and reduce inference costs over time.
πŸŽ“
AI Model Comparison and Evaluation
Research teams and AI engineers use Vellum to run side-by-side evaluations of GPT-4, Claude, Mistral, and other models against custom test datasets. This allows them to select the best-performing model for their specific use case with data-backed confidence.
πŸ’Ό
Enterprise AI Application Deployment
Enterprise engineering teams use Vellum to productionize LLM-powered features with version control, deployment management, and rollback capabilities. They reduce time-to-deployment and maintain governance over AI outputs in regulated environments.

πŸ’¬ Frequently Asked Questions

Is vellam free to use? β–Ό
Vellum offers a Freemium model with a free tier that allows teams to get started building and testing LLM workflows at no cost. Paid plans unlock higher usage limits, advanced features like custom evaluations, and priority support. Pricing scales based on usage and team size, with Pro plans typically starting around $20-$50 per month.
How does vellam compare to ChatGPT? β–Ό
Vellum is a developer and enterprise-focused platform for building, deploying, and monitoring LLM-powered applications, while ChatGPT is a consumer-facing conversational AI tool. Vellum supports multi-provider model access, prompt versioning, workflow chaining, and production observabilityβ€”features ChatGPT does not offer. It is designed for teams shipping AI products, not for general end-user conversations.
What can I do with vellam? β–Ό
With Vellum, you can design and test prompts in a collaborative playground, build multi-step AI workflows with branching logic, and evaluate LLM outputs against custom datasets. It also supports deployment management, A/B testing of prompts, and real-time monitoring of live AI applications. Integrations with models like GPT-4, Claude, Llama, and Mistral are built in.
Is vellam safe and private? β–Ό
Vellum follows enterprise-grade security practices including SOC 2 Type II compliance, ensuring that customer data is handled with strong access controls and audit logging. Data submitted through the platform is not used to train third-party models by default. Teams can review Vellum's privacy policy and data processing agreements for specifics relevant to regulated industries.
How do I get started with vellam? β–Ό
To get started, visit vellum.ai and sign up for a free account using your work email. After onboarding, you can connect your LLM provider API keys, create your first prompt in the Prompt Sandbox, and begin building workflows immediately. Vellum also provides documentation, starter templates, and a support team to help accelerate your first deployment.
What are the limitations of vellam? β–Ό
Vellum's free tier has usage caps that may restrict larger teams or high-volume production workloads. While it supports many major LLM providers, some niche or self-hosted models may require additional configuration. The platform is primarily designed for technical users, so non-technical stakeholders may face a steeper learning curve compared to simpler no-code AI tools.

πŸ‘€ About the Founder

Akash Sharma
Akash Sharma
CEO & Co-Founder Β· Vellum AI
Akash Sharma previously worked as a software engineer and product leader at companies including Flexport and Thumbtack, gaining deep expertise in developer tooling and workflow automation. He co-founded Vellum alongside technical co-founders to address the painful gap between LLM prototyping and reliable production deployment. Frustrated by the lack of structured tooling for prompt management and evaluation, he built Vellum to give engineering and product teams the infrastructure needed to ship AI features confidently.

⭐ User Reviews

β˜…β˜…β˜…β˜…β˜…
Vellum's Prompt Sandbox made it incredibly easy to test and compare outputs from GPT-4 and Claude side by side before committing to a final template. The version control for prompts alone saved our team hours of manual tracking every week.
SK
Sarah K.
Content Manager
2025-11-15
β˜…β˜…β˜…β˜…β˜…
The workflow builder in Vellum allowed me to chain multiple LLM calls with conditional logic in a way that would have taken weeks to build from scratch. I docked one star only because some advanced evaluation features are locked behind higher-tier plans.
JT
James T.
Software Engineer
2025-10-20
β˜…β˜…β˜…β˜…β˜…
We used Vellum's evaluation and monitoring tools to measure output quality across our AI content pipeline, which gave us the confidence to scale production without sacrificing accuracy. The real-time observability dashboard is genuinely one of the best I've seen in any LLM tooling platform.
PM
Priya M.
Marketing Director
2025-09-10
🌐 Visit Website
vellum.ai
Vellam
Personal AI that works for you
πŸ“€ Share This Tool
ℹ️ Quick Info
CategoryπŸ€– Chatbots & GPTs
DeveloperVellum AI
PlatformWeb, iOS, Android
AccessFreemium
Rating⭐ 4.7/5
Launched2022
🏷️ Tags
πŸ€– Chatbots & GPTsFreemiumVellum AIAIVellam

πŸ”₯ More Tools You Might Like