Vellum vs Langflow: Features, Pricing and User Reviews 2026
What are Vellum and Langflow?
Vellum is a platform that helps you create AI applications from start to finish. You can build chatbots, content tools, data analysis systems, or custom AI assistants. The platform works with all major AI models including GPT-4, Claude, and open source options.
What makes Vellum different is its agent builder. You describe what you want your AI to do in plain language, and it automatically creates the workflow. You can connect your AI to business tools like HubSpot, Slack, and Google Drive. The platform includes testing tools to check quality before launch and monitoring to track how well things work after launch.
Both technical and non-technical team members can use Vellum. Developers set up connections and security, while other team members adjust prompts and workflows without touching code.
Langflow is an open-source platform for building AI applications through a visual interface. You create workflows by connecting building blocks called components. Each component performs a specific task, such as loading data, talking to an AI model, or storing information in a database.
The platform supports agents that can make decisions, use tools, and perform multiple tasks automatically. It also enables Retrieval Augmented Generation (RAG), which lets AI applications search through your documents and provide accurate answers based on your specific data.
There is no cost to use Langflow. It's completely free and open-source. You only pay for external services you connect to it, such as AI model providers like OpenAI or cloud hosting if you choose to deploy your application online.
Features of Vellum and Langflow
Build AI agents by describing tasks in plain language
Visual workflow builder with drag-and-drop interface
Support for GPT-4, Claude, and open source models
Document upload and intelligent search capabilities
Real-time testing and quality evaluations
One-click deployment with API access
Version control and rollback options
Performance monitoring and cost tracking
Team collaboration tools
Integration with business software
Visual drag-and-drop workflow builder
Support for multi-agent AI systems
RAG (Retrieval Augmented Generation) capabilities
Compatible with all major AI models
Custom component creation with Python
Automatic API generation for workflows
Real-time testing and debugging tools
Integration with vector databases
Pre-built templates and examples
Open-source and completely free
Desktop and web-based versions
Use Cases of Vellum and Langflow
Pricing of Vellum and Langflow
Vellum offers flexible pricing plans designed for different team sizes and needs.
The Startup Plan is designed for teams looking to use Vellum's complete product suite to build strong AI applications. This plan includes prompt engineering tools, workflow creation through both the visual interface and code, document retrieval with smart search, testing tools for quality checks, deployment options, and monitoring capabilities. Teams get up to 5 user accounts. Pricing is custom based on your needs, and you can book a demo to discuss details.
The Enterprise Plan is built for larger companies with specific requirements and need for extra support. This plan includes everything in the Startup plan plus role-based access control to manage permissions, multiple workspaces for different teams or projects, option to install in your own cloud environment, connections to external monitoring tools, single sign-on for easy access, custom contracts with security agreements, dedicated support with guaranteed response times, and custom number of users. Contact their team to discuss pricing and get a personalized quote.
Langflow is completely free to use because it is open-source software. You can download it and run it on your own computer without any cost. There are no subscription fees, usage limits, or hidden charges for the software itself.
However, building AI applications requires some external services that do have costs. You'll need API keys from AI providers like OpenAI, which charges based on how much you use their models. If you connect to vector databases like Pinecone for storing information, those services have their own pricing. Most offer free tiers to get started.
For hosting, you can run Langflow on your own computer for free, or deploy it to cloud services like AWS or Google Cloud, which charge based on server usage. Many cloud providers offer free tiers or credits for new users. You have complete control over which services you use and how much you spend.
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