Velvet

Velvet helps engineering teams manage large language model (LLM) operations in production environments. It automatically logs all AI requests to your own database, enabling performance analysis, cost optimization through caching, and continuous monitoring of AI features. Teams can run experiments, compare models, and generate datasets for fine-tuning – all through SQL queries and developer-friendly workflows.

1. 1

   SQL Log Analysis

   Query LLM request logs directly in your database using SQL

2. 2

   Intelligent Caching

   Reduce costs and latency by reusing identical AI responses

3. 3

   Continuous Monitoring

   Track production AI features with automated alerts for failures

4. 4

   Dataset Generation

   Create training datasets from production logs for fine-tuning

5. 5

   Model Experiments

   Test multiple LLMs/settings against real-world usage metrics

• 📊
  Analyze LLM performance metrics
• ⚡
  Optimize costs with request caching
• 🔬
  Compare model versions through experiments
• 📈
  Generate fine-tuning datasets from logs