Vellum

Vellum is an AI development platform designed to help organizations create, deploy, and manage features powered by large language models (LLMs). By offering a suite of tools for workflow automation, document analysis, and content generation, it enables teams to integrate AI capabilities into their products and daily operations with minimal friction.

The platform includes robust features such as model fine-tuning, workflow automation for increased operational efficiency, real-time monitoring, and comprehensive evaluation tools to test models prior to deployment. It also supports integration with Microsoft Azure hosted OpenAI models, broadening the spectrum of deployment scenarios. Security is a strong component, with compliance coverage for standards like SOC2 and HIPAA.

Vellum is built for scalability, making it appropriate for both small teams and large enterprises. Its collaborative capabilities allow technical and non-technical users to work together efficiently, while continuous improvement options mean that teams can keep refining their AI-driven features in production. While highly capable, Vellum does come with some learning curve and requires reliance on third-party model providers. Pricing information is offered on request, indicating a tailored approach for varied organizational needs.

Vellum is best suited for product and engineering teams in organizations seeking to integrate advanced language model features into their offerings or internal workflows. It is particularly valuable to technology startups, medium to large companies, and enterprises in sectors like healthcare, education, and customer service where automation, document analysis, and sensitive data handling are important.

Product managers and CTOs can use Vellum to lead the development, fine-tuning, and monitoring of AI features, enabling rapid prototyping and deployment of LLM-based functionalities. Software developers benefit from streamlined workflows and robust evaluation tools that facilitate iterative improvement and reliable rollouts. The platform is also useful for non-machine learning professionals who need to implement high-quality AI-driven solutions without requiring deep AI expertise. Its collaboration and compliance features make it an appealing choice for cross-functional teams working on mission-critical applications.