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Vellum AI

Vellum AI

Vellum AI is an end-to-end platform for AI product teams focused on AI agents and application development. It provides a visual workflow designer, prompt engineering, multi-model testing and evaluation, and one-click deployment to help you build, test, and deploy LLM-powered applications more efficiently from concept to production.
Rating:
5
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AI agent development platformLLM application development toolsvisual AI workflowsprompt engineering and testingRAG (Retrieval-Augmented Generation)multi-model comparison and evaluationAI application deployment monitoringenterprise process automation

Features of Vellum AI

A visual workflow designer with drag-and-drop operations and SDK support, enabling the construction of complex AI pipelines that include model calls, retrieval, and post-processing.
Supports prompt engineering with templated design, version comparisons, team collaboration, and version control.
Built-in evaluation and testing system for quantitative assessment and cohort testing of prompts, models, or strategies using prebuilt or custom metrics.
Provides Retrieval-Augmented Generation (RAG) capabilities with document uploads, semantic search, and vector database integration for easy access to enterprise knowledge bases.
Compatible with a range of popular open-source and proprietary LLMs, with a unified API to compare and optimize quality, cost, and latency.
One-click deployment of developed workflows as online API services, with production-grade monitoring to track performance metrics and error logs.
Integrations with popular enterprise tools (Notion, Slack, Salesforce) to pull data and deliver results.
Supports converting workflows from tools like n8n into Vellum agents to simplify migration and accelerate integrations.
Access to expert blogs and LLM rankings to inform users about AI trends and model performance.

Use Cases of Vellum AI

Product managers can pull roadmaps from Notion or Linear, factor in team capacity and historical data, and identify risks in project planning.
Customer success teams need to consolidate PostHog usage data with Salesforce account data to detect declining usage trends and flag at-risk accounts.
Dev teams want to build an intelligent chat assistant and iterate prompts quickly, run multi-model tests, and evaluate performance.
Enterprises can build a knowledge-base Q&A system from internal documents, enabling semantic search and accurate content generation.
Operations teams need to automatically generate weekly team updates, summarizing Linear task statuses, PR details, and release notes, and publish to Slack and Notion.
Content teams need bulk content generation, summaries, or SEO optimization, with centralized management of prompt templates and output quality assessment.
Developers want to migrate existing workflows like n8n to a platform focused on AI agent development to accelerate LLM feature integration.
Data scientists need to run comparative experiments across different LLMs to evaluate performance, cost, and latency and choose the best deployment strategy.

FAQ about Vellum AI

QWhat is Vellum AI? What does it do?

Vellum AI is an end-to-end platform focused on AI agents and application development. It helps AI product teams by providing visual workflow development, prompt engineering, multi-model testing and evaluation, and one-click deployment to build, test, and deploy LLM-powered applications more efficiently.

QWho is Vellum AI platform for?

The platform is aimed at product teams who develop and deploy AI applications, including product managers, software engineers, data scientists, and operations staff. It offers both low-code visual interfaces and a professional SDK for development, enabling collaboration across different technical backgrounds.

QDo you need programming skills to use Vellum AI?

Vellum AI provides a visual drag-and-drop workflow interface for building automation, lowering the technical barrier. For advanced use, it also offers Python/TypeScript SDK and code execution capabilities to meet more complex, customized development needs.

QWhich large language models does Vellum AI support?

The platform supports integration with multiple major open-source and proprietary LLM providers, such as OpenAI and Anthropic, with a unified interface to compare and switch between models in terms of quality, cost, and latency.

QHow is Vellum AI priced? Is there a free version?

The platform offers several pricing plans, including a free plan. The free plan includes a limited quota and basic features. Professional, Commercial, and Enterprise/custom editions provide more credits, higher concurrency, longer data retention, and dedicated support. For exact pricing and quotas, refer to the latest pricing page on the official site.

QHow does Vellum AI handle data security and privacy?

According to its public information, the platform offers different data retention options. For details on data encryption, storage locations, and compliance measures, please review its official privacy policy and terms of service, or contact their sales team.

QWhat specific automation tasks can Vellum AI do?

It can be used to build a variety of intelligent agents, such as automatically extracting data from tools to generate analyses, monitoring risk accounts to generate alert lists, automatically summarizing project status and publishing weekly reports, and building knowledge-base-based Q&A systems.

QHow is Vellum AI different from workflow tools like n8n?

Vellum AI focuses more on AI agents and large language model applications. It simplifies connecting LLMs, performing prompt engineering, and evaluating results, and supports migrating existing workflows from tools like n8n onto its platform to accelerate AI feature integration and development.

QHow to get started with Vellum AI?

You can usually start by signing up for a free account, exploring the platform's ready-to-use templates and visual development environment. The website also provides product demos, case studies, and documentation to help users quickly get started.

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