• Vellum AI

  • Vellum AI is a platform for building, testing, deploying and monitoring large language-model (LLM)-powered applications. It offers tools for prompt engineering, workflow automation, versioning, evaluation, and observability.

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About Tool

Vellum AI is designed for organizations and teams working on large language model (LLM) applications. Instead of relying on multiple disconnected tools for prompt testing, evaluation, workflow automation, and observability, Vellum consolidates them into a single platform. This makes it easier for both technical and non-technical users to collaborate on building, optimizing, and deploying AI-driven applications. By offering version control, monitoring, and enterprise-level compliance, it ensures a smoother path from prototype to production.

Key Features

  • Prompt Engineering & Testing: Experiment with and refine prompts through side-by-side comparisons.
  • Workflow Builder: Create and manage complex workflows using low-code or visual tools.
  • Versioning & Release Management: Track iterations, manage releases, and roll back if needed.
  • Evaluation Framework: Run quantitative and qualitative tests to ensure accuracy and reliability.
  • Deployment & Observability: Monitor live systems with trace and graph views for transparency.
  • Document Retrieval & Semantic Search: Provide context to prompts with advanced search capabilities.
  • Enterprise-Grade Security: Role-based access, data retention policies, and compliance support.

Pros:

  • Comprehensive: Covers the full lifecycle of AI app development in one platform.
  • Monitoring: Strong observability tools to track and optimize production workflows.
  • Collaboration: Allows both technical and non-technical users to contribute effectively.
  • Compliance: Enterprise-level features for security and regulated industries.

Cons:

  • Pricing: Requires contacting sales for full details, limiting transparency.
  • Learning Curve: Can be overwhelming for smaller teams or beginners.
  • Overhead: May be more than necessary for simple, small-scale projects.

Who is Using?

  • AI Engineers & Developers: Building production-ready LLM applications.
  • Product Teams: Collaborating on AI-driven features without heavy coding.
  • Startups: Speeding up prototyping while maintaining control over deployments.
  • Enterprises: Needing compliance, scalability, and secure AI application management.

Pricing

Vellum AI follows a custom pricing model tailored to team size and feature needs. Plans are available for startups, professional teams, and enterprises, with details provided upon request through demos or sales inquiries.

What Makes Unique?

Vellum AI stands out for unifying every stage of LLM app development—prompt design, workflow automation, testing, deployment, and monitoring—into one cohesive system. Its combination of visual workflows and enterprise-grade observability ensures both ease of use and production reliability.

How We Rated It:

  • Ease of Use: ⭐⭐⭐⭐☆ (4/5) — Accessible but requires onboarding.
  • Features: ⭐⭐⭐⭐⭐ (5/5) — Comprehensive lifecycle management.
  • Value for Money: ⭐⭐⭐⭐☆ (4/5) — Strong offering but pricing transparency could improve.

Vellum AI is a robust solution for teams that want to build, test, and scale LLM-powered applications with confidence. Its wide feature set makes it especially valuable for startups and enterprises developing complex or mission-critical AI solutions. While it may feel excessive for small projects, it’s an excellent investment for organizations needing reliability, compliance, and streamlined AI workflows.

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Vellum AI

About Tool

Vellum AI is designed for organizations and teams working on large language model (LLM) applications. Instead of relying on multiple disconnected tools for prompt testing, evaluation, workflow automation, and observability, Vellum consolidates them into a single platform. This makes it easier for both technical and non-technical users to collaborate on building, optimizing, and deploying AI-driven applications. By offering version control, monitoring, and enterprise-level compliance, it ensures a smoother path from prototype to production.

Key Features

  • Prompt Engineering & Testing: Experiment with and refine prompts through side-by-side comparisons.
  • Workflow Builder: Create and manage complex workflows using low-code or visual tools.
  • Versioning & Release Management: Track iterations, manage releases, and roll back if needed.
  • Evaluation Framework: Run quantitative and qualitative tests to ensure accuracy and reliability.
  • Deployment & Observability: Monitor live systems with trace and graph views for transparency.
  • Document Retrieval & Semantic Search: Provide context to prompts with advanced search capabilities.
  • Enterprise-Grade Security: Role-based access, data retention policies, and compliance support.

Pros:

  • Comprehensive: Covers the full lifecycle of AI app development in one platform.
  • Monitoring: Strong observability tools to track and optimize production workflows.
  • Collaboration: Allows both technical and non-technical users to contribute effectively.
  • Compliance: Enterprise-level features for security and regulated industries.

Cons:

  • Pricing: Requires contacting sales for full details, limiting transparency.
  • Learning Curve: Can be overwhelming for smaller teams or beginners.
  • Overhead: May be more than necessary for simple, small-scale projects.

Who is Using?

  • AI Engineers & Developers: Building production-ready LLM applications.
  • Product Teams: Collaborating on AI-driven features without heavy coding.
  • Startups: Speeding up prototyping while maintaining control over deployments.
  • Enterprises: Needing compliance, scalability, and secure AI application management.

Pricing

Vellum AI follows a custom pricing model tailored to team size and feature needs. Plans are available for startups, professional teams, and enterprises, with details provided upon request through demos or sales inquiries.

What Makes Unique?

Vellum AI stands out for unifying every stage of LLM app development—prompt design, workflow automation, testing, deployment, and monitoring—into one cohesive system. Its combination of visual workflows and enterprise-grade observability ensures both ease of use and production reliability.

How We Rated It:

  • Ease of Use: ⭐⭐⭐⭐☆ (4/5) — Accessible but requires onboarding.
  • Features: ⭐⭐⭐⭐⭐ (5/5) — Comprehensive lifecycle management.
  • Value for Money: ⭐⭐⭐⭐☆ (4/5) — Strong offering but pricing transparency could improve.

Vellum AI is a robust solution for teams that want to build, test, and scale LLM-powered applications with confidence. Its wide feature set makes it especially valuable for startups and enterprises developing complex or mission-critical AI solutions. While it may feel excessive for small projects, it’s an excellent investment for organizations needing reliability, compliance, and streamlined AI workflows.

Product Image
Product Video

Vellum AI

About Tool

Vellum AI is designed for organizations and teams working on large language model (LLM) applications. Instead of relying on multiple disconnected tools for prompt testing, evaluation, workflow automation, and observability, Vellum consolidates them into a single platform. This makes it easier for both technical and non-technical users to collaborate on building, optimizing, and deploying AI-driven applications. By offering version control, monitoring, and enterprise-level compliance, it ensures a smoother path from prototype to production.

Key Features

  • Prompt Engineering & Testing: Experiment with and refine prompts through side-by-side comparisons.
  • Workflow Builder: Create and manage complex workflows using low-code or visual tools.
  • Versioning & Release Management: Track iterations, manage releases, and roll back if needed.
  • Evaluation Framework: Run quantitative and qualitative tests to ensure accuracy and reliability.
  • Deployment & Observability: Monitor live systems with trace and graph views for transparency.
  • Document Retrieval & Semantic Search: Provide context to prompts with advanced search capabilities.
  • Enterprise-Grade Security: Role-based access, data retention policies, and compliance support.

Pros:

  • Comprehensive: Covers the full lifecycle of AI app development in one platform.
  • Monitoring: Strong observability tools to track and optimize production workflows.
  • Collaboration: Allows both technical and non-technical users to contribute effectively.
  • Compliance: Enterprise-level features for security and regulated industries.

Cons:

  • Pricing: Requires contacting sales for full details, limiting transparency.
  • Learning Curve: Can be overwhelming for smaller teams or beginners.
  • Overhead: May be more than necessary for simple, small-scale projects.

Who is Using?

  • AI Engineers & Developers: Building production-ready LLM applications.
  • Product Teams: Collaborating on AI-driven features without heavy coding.
  • Startups: Speeding up prototyping while maintaining control over deployments.
  • Enterprises: Needing compliance, scalability, and secure AI application management.

Pricing

Vellum AI follows a custom pricing model tailored to team size and feature needs. Plans are available for startups, professional teams, and enterprises, with details provided upon request through demos or sales inquiries.

What Makes Unique?

Vellum AI stands out for unifying every stage of LLM app development—prompt design, workflow automation, testing, deployment, and monitoring—into one cohesive system. Its combination of visual workflows and enterprise-grade observability ensures both ease of use and production reliability.

How We Rated It:

  • Ease of Use: ⭐⭐⭐⭐☆ (4/5) — Accessible but requires onboarding.
  • Features: ⭐⭐⭐⭐⭐ (5/5) — Comprehensive lifecycle management.
  • Value for Money: ⭐⭐⭐⭐☆ (4/5) — Strong offering but pricing transparency could improve.

Vellum AI is a robust solution for teams that want to build, test, and scale LLM-powered applications with confidence. Its wide feature set makes it especially valuable for startups and enterprises developing complex or mission-critical AI solutions. While it may feel excessive for small projects, it’s an excellent investment for organizations needing reliability, compliance, and streamlined AI workflows.

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