Velvet Logs, Analyzes and Manages AI Requests Directly In Your Database
Ellen Smith — February 27, 2025 — Tech
References: usevelvet
Velvet is a tool designed to log and store all AI requests directly into a user’s own database, providing a structured and queryable record of interactions with AI models. With only two lines of code needed for installation, it acts as a lightweight proxy between applications and AI services.
This allows developers and organizations to monitor usage patterns, track costs, and evaluate model performance over time. Velvet also supports the creation of custom datasets based on real-world interactions, which can be useful for refining prompts or training new models. By storing the data locally, users retain full ownership and control over their data, which can be advantageous for businesses with strict compliance or data governance requirements. Velvet offers a straightforward way to add transparency and analytics to AI usage workflows.
Image Credit: Velvet
This allows developers and organizations to monitor usage patterns, track costs, and evaluate model performance over time. Velvet also supports the creation of custom datasets based on real-world interactions, which can be useful for refining prompts or training new models. By storing the data locally, users retain full ownership and control over their data, which can be advantageous for businesses with strict compliance or data governance requirements. Velvet offers a straightforward way to add transparency and analytics to AI usage workflows.
Image Credit: Velvet
Trend Themes
1. AI Usage Analytics - Developers can gain insights into AI interactions and usage patterns by leveraging Velvet's ability to log and analyze AI requests in real-time.
2. Data Ownership Models - Velvet empowers organizations to maintain full control and ownership of their AI interaction data, supporting stronger compliance and data governance efforts.
3. Custom Dataset Creation - The capability to generate tailored datasets from real-world AI interactions presents a new avenue for tuning AI models and improving prompt accuracy.
Industry Implications
1. Database Management - Integrating AI request logging directly into databases opens up new opportunities for improving database transparency and performance analysis.
2. AI Development - Tools like Velvet introduce new methods for monitoring model performance and facilitating data-driven refinements in AI development projects.
3. Data Compliance - Velvet supports industries with stringent data handling practices by providing localized storage of AI interaction data, enhancing data compliance capabilities.
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