Vellum AI

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Vellum AI builds LLM applications with prompt engineering, testing, monitoring, and no-code workflows for enhanced collaboration.

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What is Vellum AI?

Vellum AI is a development platform designed for building Large Language Model (LLM) applications. It provides tools for prompt engineering, semantic search, version control, testing, monitoring, and collaboration. Users can compare, test, and collaborate on prompts and models, and incorporate proprietary data to enhance accuracy. Vellum AI supports efficient deployment, versioning, and monitoring of LLM changes, offers a no-code LLM builder, workflow automation, and various AI functionalities like chatbots, sentiment analysis, and more. Customers appreciate its ease of use, fast deployment, monitoring capabilities, and collaborative workflows.

Who created Vellum AI?

Vellum was created by Daniel Weiner, who is the Founder at Autobound. The platform was launched on November 29, 2023, offering a development platform specifically designed for building Large Language Model (LLM) applications. Vellum provides tools for prompt engineering, semantic search, version control, testing, monitoring, and collaboration. It is compatible with all major LLM providers, enabling users to bring LLM-powered features to production through prompt engineering tools.

What is Vellum AI used for?

Chatbots
Summarization
Workflow automation
Sentiment Analysis
Data extraction
Document analysis
Topic summarizer
Vector search
Dialogue generation
Blog generator
Email generator
Prompt engineering on steroids
Compose Complex Multi-Step Chains
Evaluate Prompts at Scale
Copilots
Fine-tuning
Q&A over Docs
Intent classification
Out-of-Box RAG
Deploy Changes With Confidence

Who is Vellum AI for?

Engineers
Artificial Intelligence Developers
Data scientists
Product teams
Engineer
Data Scientist
AI application developer
AI experts
Startups
AI teams
Developers
Co-Founder & CEO
Co-Founder & CTO
Founder & CEO
Partner & CTO
Founder
VP of Technology and Design
Full Stack Engineer
AI Product Manager
Senior Product Manager
Lead Developer
Head of Operations
Chief Scientific Officer
Founder @ Autobound
VP of Technology and Design @ Rentgrata
Full Stack Engineer @ Lavender
Partner & CTO at Left Field Labs

How to use Vellum AI?

To use Vellum, follow these steps:

Prompt Engineering: Experiment with new prompts and models without affecting production. Evaluate prompts using quantitative metrics or define your own.
Compose Complex Chains: Prototype, test, and deploy complex chains of prompts and logic with versioning, debugging, and monitoring tools.
Out-of-Box RAG: Quickly start with RAG (Retrieve And Generate) functionality without backend infrastructure overhead.
Deployment: Manage prompt and prompt chain changes with release management similar to GitHub. Monitor performance and catch edge cases in production.
Testing & Evaluation: Utilize test suites to evaluate LLM outputs at scale and ensure quality.
No-Code LLM Builder: Build various LLM-powered applications without coding skills.
Additional Features: Workflow automation, document analysis, copilots, Q&A over docs, intent classification, summarization, sentiment analysis, chatbots, and more.
Customer Feedback: Users praise Vellum for ease of use, fast deployment, detailed monitoring, and prompt testing capabilities.
Flexibility: Choose the best LLM provider and model for specific tasks without vendor lock-in.
Collaboration: Facilitate collaborative workflows to streamline development, deployment, and monitoring processes.

Vellum provides a comprehensive platform for building LLM applications, offering tools for experimentation, evaluation, deployment, and monitoring. With a wide range of features and flexibility in LLM utilization, Vellum is a valuable tool for development teams aiming to leverage AI capabilities effectively .

Pros

Provides peace of mind for debugging production LLM traffic
Flexible to choose the best LLM provider and model for specific tasks
Customers appreciate ease of use, fast deployment, and detailed monitoring
Features workflow automation and various AI functionalities like chatbots and sentiment analysis
Offers no-code LLM builder for building applications without coding skills
Provides testing capabilities at scale to ensure quality of outputs
Supports incorporating proprietary data for enhanced accuracy
Enables efficient deployment, versioning, and monitoring of LLM changes
Vellum has completely transformed the company's LLM development process with a 5x improvement in productivity
Clean UI for observing abnormalities and making changes without breaking existing behavior
Comprehensive solution for development teams seeking to leverage LLM capabilities
Allows multiple disciplines within a company to collaborate on AI workflows
Variety of functionalities for AI applications
Comprehensive solution for development teams leveraging LLM capabilities
Flexibility to choose the best LLM provider and model

Cons

No cons were identified in the provided content.
No information provided on potential cons of using Vellum in the documents.
No information on cons is available in the provided documents.

Pros

Cons

Provides peace of mind for debugging production LLM traffic
Flexible to choose the best LLM provider and model for specific tasks
Customers appreciate ease of use, fast deployment, and detailed monitoring
Features workflow automation and various AI functionalities like chatbots and sentiment analysis
Offers no-code LLM builder for building applications without coding skills
Provides testing capabilities at scale to ensure quality of outputs
Supports incorporating proprietary data for enhanced accuracy
Enables efficient deployment, versioning, and monitoring of LLM changes
Vellum has completely transformed the company's LLM development process with a 5x improvement in productivity
Clean UI for observing abnormalities and making changes without breaking existing behavior
Comprehensive solution for development teams seeking to leverage LLM capabilities
Allows multiple disciplines within a company to collaborate on AI workflows
Variety of functionalities for AI applications
Comprehensive solution for development teams leveraging LLM capabilities
Flexibility to choose the best LLM provider and model

No cons were identified in the provided content.
No information provided on potential cons of using Vellum in the documents.
No information on cons is available in the provided documents.

Vellum AI FAQs

What is Vellum?: Vellum is a development platform specifically designed for building Large Language Model (LLM) applications

What features does Vellum offer?: Vellum offers prompt engineering, semantic search, version control, testing, monitoring, workflow automation, document analysis, copilots, fine-tuning, Q&A over documents, intent classification, summarization, vector search, sentiment analysis, chatbots, and LLM evaluation functionalities

How does Vellum support developers in deploying Large Language Models?: Vellum supports efficient deployment, versioning, and monitoring of LLM changes in production, providing a streamlined workflow for complex LLM chains

What are some notable features of Vellum?: Some notable features of Vellum include its no-code LLM builder, workflow automation, collaborative workflows, detailed production monitoring, and fast deployment capabilities

How does Vellum enable comparison and collaboration on prompts and models?: Vellum enables users to compare, test, and collaborate on prompts and models, incorporating proprietary data as context in LLM calls to enhance accuracy of results

What customer benefits does Vellum offer?: Vellum provides customers with ease of use, fast deployment, detailed production monitoring, prompt testing capabilities, and collaborative workflows, allowing for the building of LLM-powered applications without extensive coding skills