Velvet
About Velvet
Velvet is an innovative AI gateway designed for engineers to streamline their workflow. Users can log requests and optimize AI features with an easy two-line implementation. Its unique logging system allows for detailed analysis and fine-tuning, helping teams maximize AI performance and minimize costs efficiently.
Velvet offers a free tier for up to 10,000 requests per month, making it easy for users to get started at no cost. As users scale, they can explore advanced pricing plans, providing more extensive features and capabilities, ensuring affordability while meeting diverse team needs.
Velvet features a user-friendly interface that facilitates seamless navigation. Its layout is designed for optimal user experience, highlighting key functionalities and allowing engineers to quickly access features like logging, optimization tools, and data analysis, making effective use of the platform's comprehensive capabilities.
How Velvet works
Users start by creating an account on Velvet, where they can easily access comprehensive documentation. After setting the base URL to the Velvet gateway, they can connect their database or use Velvet’s storage. The platform facilitates logging of all requests, enabling efficient analysis, optimization, and experimentations with minimal setup.
Key Features for Velvet
Request Logging
Velvet's request logging feature allows users to warehouse every OpenAI and Anthropic request in their PostgreSQL database. This unique capability enables engineers to analyze and evaluate their AI models, making it easier to fine-tune features and optimize performance based on real usage data.
Optimized Caching
Velvet's optimized caching system reduces latency and costs significantly by enabling intelligent data storage choices. This feature streamlines engineers' processes, allowing faster response times and efficient use of OpenAI's Batch and Files APIs, enhancing the platform's overall performance and user efficiency.
Experimentation Framework
The experimentation framework in Velvet allows users to run diverse tests on datasets, facilitating model fine-tuning and optimization. With this feature, engineers can strategically evaluate different models, prompting settings, and metrics for enhanced performance, making Velvet a reliable tool for AI development.
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