Velvet
About Velvet
Velvet is an innovative AI gateway designed for engineers to analyze and optimize their AI features effortlessly. By simply adding two lines of code, users can warehouse OpenAI and Anthropic requests to a PostgreSQL database, allowing for easy monitoring, analysis, and cost reduction.
Velvet offers a free tier for up to 10k requests monthly, allowing users to start without initial costs. As users grow, they can explore premium plans that enhance storage capabilities and advanced features, maximizing their efficiency and optimizing AI usage while ensuring scalability.
Velvet features a clean, user-friendly interface that simplifies navigation and management of database logs and AI experiments. Its seamless layout ensures users can access tools effortlessly, enhancing their experience while monitoring API usage and optimizing performance with real-time insights.
How Velvet works
Users begin by creating an account on Velvet's platform and then reading the documentation to understand the setup process. By setting the baseURL to the Velvet gateway and connecting their database, they can log every request made to their AI models. With data warehoused in PostgreSQL, users can analyze and evaluate AI performance, implement caching strategies, and conduct experiments, all facilitated by Velvet's robust framework and intuitive interface.
Key Features for Velvet
Warehouse AI Requests
Velvet's unique ability to warehouse every AI request to a PostgreSQL database gives engineers a clear data source for analysis. This feature enhances users' insights into AI models' performance, enabling effective optimizations and fine-tuning for improved outcomes.
Granular Observability
With Velvet's granular observability, users can store data in customizable JSON formats, allowing for detailed analysis of API usage and costs. This feature helps engineers optimize AI features, troubleshoot issues effectively, and monitor their models comprehensively, enhancing overall productivity.
Intelligent Caching System
Velvet's intelligent caching system reduces costs and latency by optimizing how data is retrieved and stored. This feature ensures quick responses for identical requests, enabling engineers to focus on development while minimizing unnecessary expenditures, enhancing operational efficiency.
FAQs for Velvet
How does Velvet help in optimizing AI features?
Velvet aids engineers in optimizing AI features by allowing them to analyze usage logs and evaluate model performance through stored data. By enabling intelligent caching and batching, Velvet reduces costs while helping users better understand their API interactions and improve overall efficiency in their workflows.
What is the process to get started with Velvet?
Getting started with Velvet is straightforward: create an account at usevelvet.com/register, read the documentation to understand setup, set your baseURL, and connect your database. These steps empower users to begin logging and optimizing their AI requests with ease and efficiency.
What unique benefits does Velvet offer for engineers?
Velvet provides numerous benefits for engineers, including seamless integration with OpenAI and Anthropic APIs, extensive data warehousing, and advanced analytics capabilities. This allows engineers to optimize their machine learning workflows, reduce operational costs, and enhance performance, thereby streamlining their development processes.
How does Velvet stand out in the AI tools market?
Velvet stands out in the AI tools market with its unique combination of AI request warehousing, intelligent caching, and comprehensive observability. These features not only enhance engineers' ability to monitor and optimize their models but also provide cost-efficiency, making Velvet a valuable asset in AI development.
What are the practical use cases for using Velvet?
Practical use cases for Velvet include analyzing model usage for optimization, implementing caching to reduce costs, running experiments on datasets, and generating training sets for fine-tuning models. These functionalities empower teams to enhance their AI projects' efficiency and effectiveness, meeting diverse engineering needs.
How does Velvet streamline the data analysis process for AI models?
Velvet streamlines the data analysis process by automating the logging of AI requests, which are warehoused in a PostgreSQL database. This eliminates manual data collection, allowing engineers to focus on deeper analysis, evaluate models more effectively, and run structured experiments that improve decision-making and resource allocation.
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